governance-platform
Pre-execution governance for AI agents. Deterministic PASS/FAIL/REVIEW verdicts, replayable proof.
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Calidad y seguridad
Hallazgos (2)
- LOWen repair
- LOWen recent_inference_decisions
Basado en el análisis automatizado de las definiciones de herramientas y el cumplimiento del protocolo.
Costo de contexto
Este es el número aproximado de tokens que se consumen cada vez que las herramientas del servidor se cargan en el contexto de un modelo. Los recuentos más altos reducen la atención disponible para otras tareas.
Instalar
Instalación con un clic
Agrega esto a tu archivo `claude_desktop_config.json`:
{
"mcpServers": {
"governance-platform": {
"url": "https://app.geodesiclabs.ai/mcp"
}
}
}Puntos de conexión remotos
https://app.geodesiclabs.ai/mcpstreamable-httpQué puede hacer
Inventario de herramientas
Herramientas (37)
⚪validate(api_key, structured_data, blueprint)
Validate structured data against a Blueprint's rules BEFORE the result is used. Returns PASS, FAIL, or REVIEW with plain-language findings, repair suggestions, a determinism hash, and a re-verifiable certificate. Same input + same rules = same verdict, every time.
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
},
"structured_data": {
"additionalProperties": true,
"description": "The document's extracted fields as key/value pairs. Keys are open by design - your Blueprint's rules define what is checked",
"title": "Structured Data",
"type": "object"
},
"blueprint": {
"default": "default",
"description": "Blueprint name (workflow_name) to use",
"title": "Blueprint",
"type": "string"
}
},
"required": [
"api_key",
"structured_data"
],
"title": "validateArguments"
}⚪validate_repair(api_key, structured_data, blueprint)
Validate structured data against a Blueprint and, when it fails, include repair suggestions (corrected values with the rule each fix is based on) in the same call. Same verdicts as validate: PASS, FAIL, or REVIEW, with reasons and proof.
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
},
"structured_data": {
"additionalProperties": true,
"description": "The document's extracted fields as key/value pairs. Keys are open by design - your Blueprint's rules define what is checked",
"title": "Structured Data",
"type": "object"
},
"blueprint": {
"default": "default",
"description": "Blueprint name (workflow_name) to use",
"title": "Blueprint",
"type": "string"
}
},
"required": [
"api_key",
"structured_data"
],
"title": "validate_repairArguments"
}🟡create_blueprint(api_key, customer_name, workflow_name, mode, extracted_fields, ...)
Create a Blueprint - the governance contract validation runs against. A Blueprint defines what correct means for your data: fields, the math that must hold between them, and acceptable ranges. Start from load_rule_pack or discover_patterns if you have no rules yet; invoke the blueprint_guide prompt for the full rule/constraint reference. Returns the new Blueprint's API key.
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
},
"customer_name": {
"description": "Organization or project name (also used for storage folder naming)",
"title": "Customer Name",
"type": "string"
},
"workflow_name": {
"description": "Unique Blueprint identifier; the value passed as 'blueprint' in validate",
"title": "Workflow Name",
"type": "string"
},
"mode": {
"default": "observe",
"description": "observe: platform checks the agent's work; enforce: platform computes derived fields itself",
"enum": [
"observe",
"enforce"
],
"title": "Mode",
"type": "string"
},
"extracted_fields": {
"default": null,
"description": "Field names the agent extracts from source data, e.g. ['vendor','qty','unit_cost']",
"items": {},
"title": "Extracted Fields",
"type": "array"
},
"derived_fields": {
"default": null,
"description": "Field names the platform computes from other fields, e.g. ['subtotal','total']",
"items": {},
"title": "Derived Fields",
"type": "array"
},
"derivation_rules": {
"default": null,
"description": "Math rules as objects. Types: add, subtract, multiply, divide, round, copy, sum (multi-operand), items_multiply, items_sum. Each needs 'type' plus its fields; see the blueprint_guide prompt",
"items": {},
"title": "Derivation Rules",
"type": "array"
},
"formal_constraints": {
"default": null,
"description": "Constraint objects. Types incl. magnitude_anchor {field,min,max}, relative_anchor {field,reference_field,ratio_min,ratio_max}, max_action_threshold {field,threshold,on_violation}, required_fields {fields}, equals, range, in_set, regex_match, items_magnitude_anchor; see the blueprint_guide prompt",
"items": {},
"title": "Formal Constraints",
"type": "array"
},
"semantic_checks": {
"default": null,
"description": "Domain-specific semantic check objects",
"items": {},
"title": "Semantic Checks",
"type": "array"
},
"require_math": {
"default": true,
"description": "Validate mathematical relationships",
"title": "Require Math",
"type": "boolean"
},
"require_consistency": {
"default": true,
"description": "Check internal field consistency",
"title": "Require Consistency",
"type": "boolean"
},
"require_coherence": {
"default": true,
"description": "Check cross-field plausibility",
"title": "Require Coherence",
"type": "boolean"
},
"require_provenance": {
"default": false,
"description": "Require extraction source locations for fields",
"title": "Require Provenance",
"type": "boolean"
},
"require_high_assurance": {
"default": false,
"description": "Strictest mode: every check must pass",
"title": "Require High Assurance",
"type": "boolean"
},
"enable_anomaly_detection": {
"default": false,
"description": "Flag records that break no rules but do not fit the reference pattern",
"title": "Enable Anomaly Detection",
"type": "boolean"
},
"enable_drift_tracking": {
"default": false,
"description": "Track pattern stability across batches",
"title": "Enable Drift Tracking",
"type": "boolean"
}
},
"required": [
"api_key",
"customer_name",
"workflow_name"
],
"title": "create_blueprintArguments"
}🟢list_blueprints(api_key)
List the Blueprints on this account with field/rule/constraint counts and mode. Use the returned workflow_name as 'blueprint' in validate.
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
}
},
"required": [
"api_key"
],
"title": "list_blueprintsArguments"
}🟢repair(api_key, structured_data, derivation_rules, formal_constraints, blueprint)
One-shot repair: return corrected values that would make failing data valid under the Blueprint. Use repair_path to see the steps instead.
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
},
"structured_data": {
"additionalProperties": true,
"description": "The document's extracted fields as key/value pairs. Keys are open by design - your Blueprint's rules define what is checked",
"title": "Structured Data",
"type": "object"
},
"derivation_rules": {
"default": null,
"description": "Math rules as objects. Types: add, subtract, multiply, divide, round, copy, sum (multi-operand), items_multiply, items_sum. Each needs 'type' plus its fields; see the blueprint_guide prompt",
"items": {},
"title": "Derivation Rules",
"type": "array"
},
"formal_constraints": {
"default": null,
"description": "Constraint objects. Types incl. magnitude_anchor {field,min,max}, relative_anchor {field,reference_field,ratio_min,ratio_max}, max_action_threshold {field,threshold,on_violation}, required_fields {fields}, equals, range, in_set, regex_match, items_magnitude_anchor; see the blueprint_guide prompt",
"items": {},
"title": "Formal Constraints",
"type": "array"
},
"blueprint": {
"default": null,
"description": "Blueprint name (workflow_name) to use",
"title": "Blueprint",
"type": "string"
}
},
"required": [
"api_key",
"structured_data"
],
"title": "repairArguments"
}🟢check_blueprint_health(api_key, blueprint, config)
Static pre-deploy analysis of a Blueprint's rule set. Returns a health verdict - healthy, acceptable, fragile, rigid, split, brittle_islands, or unsatisfiable - with advice, including joint conflicts pairwise checks miss.
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
},
"blueprint": {
"default": "",
"description": "Blueprint name (workflow_name) to use",
"title": "Blueprint",
"type": "string"
},
"config": {
"additionalProperties": true,
"default": null,
"description": "Raw blueprint config with derivation_rules and formal_constraints (used when 'blueprint' is not given)",
"title": "Config",
"type": "object"
}
},
"required": [
"api_key"
],
"title": "check_blueprint_healthArguments"
}🟢compare_semantic_equivalence(api_key, payload_a, payload_b, field_mapping, rules_a, ...)
Compare two payloads under the dual-hash design: content_hash is content_hash normalizes field order and numeric formatting. Semantic comparison preserves field roles; renaming requires an explicit bijection. With supplied rules, scalar types and whitespace remain significant. Structural similarity alone does not establish decision equivalence.
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
},
"payload_a": {
"additionalProperties": true,
"description": "First structured payload (arbitrary JSON object)",
"title": "Payload A",
"type": "object"
},
"payload_b": {
"additionalProperties": true,
"description": "Second structured payload to compare against payload_a",
"title": "Payload B",
"type": "object"
},
"field_mapping": {
"additionalProperties": true,
"default": null,
"description": "Explicit one-to-one field renaming from A to B",
"title": "Field Mapping",
"type": "object"
},
"rules_a": {
"default": null,
"description": "Derivation rules for A",
"items": {},
"title": "Rules A",
"type": "array"
},
"rules_b": {
"default": null,
"description": "Derivation rules for B",
"items": {},
"title": "Rules B",
"type": "array"
},
"constraints_a": {
"default": null,
"description": "Formal constraints for A",
"items": {},
"title": "Constraints A",
"type": "array"
},
"constraints_b": {
"default": null,
"description": "Formal constraints for B",
"items": {},
"title": "Constraints B",
"type": "array"
}
},
"required": [
"api_key",
"payload_a",
"payload_b"
],
"title": "compare_semantic_equivalenceArguments"
}🟢govern_inference(api_key, task_type, payload, inference_id, constraints, ...)
Quality-govern an in-progress AI generation step BEFORE its output is used (complements validate, which checks finished documents). Returns an action - STOP, CONTINUE, REPAIR_REGION, REUSE_MOTIF, REVIEW, ESCALATE - with a plain-language explanation. Structural scores do not establish task correctness. Check safe_to_finalize and acceptance coverage. Persistence success is reported; read traces in the same Blueprint namespace.
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
},
"task_type": {
"description": "Kind of generation step being governed",
"enum": [
"generative_text",
"retrieval",
"generic"
],
"title": "Task Type",
"type": "string"
},
"payload": {
"additionalProperties": true,
"description": "Task-type payload: generative_text {text,...}; retrieval {query,candidates}; generic {features}",
"title": "Payload",
"type": "object"
},
"inference_id": {
"description": "Caller-chosen ID grouping the steps of one generation",
"title": "Inference Id",
"type": "string"
},
"constraints": {
"additionalProperties": true,
"default": null,
"description": "Optional governance constraint config object",
"title": "Constraints",
"type": "object"
},
"source": {
"default": "mcp",
"description": "Free-form caller label recorded for audit",
"title": "Source",
"type": "string"
},
"step_index": {
"default": 0,
"description": "Step number within this generation (0-based)",
"title": "Step Index",
"type": "integer"
},
"blueprint": {
"default": "default",
"description": "Owned Blueprint namespace for the trace",
"title": "Blueprint",
"type": "string"
}
},
"required": [
"api_key",
"task_type",
"payload",
"inference_id"
],
"title": "govern_inferenceArguments"
}🟢get_inference_trace(api_key, inference_id, blueprint, blueprint_version)
Retrieve the durable audit trail for a governed generation: every recorded decision and its reasons.
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
},
"inference_id": {
"description": "Caller-chosen ID grouping the steps of one generation",
"title": "Inference Id",
"type": "string"
},
"blueprint": {
"default": "default",
"description": "Blueprint namespace used when recording the trace",
"title": "Blueprint",
"type": "string"
},
"blueprint_version": {
"default": "",
"description": "Optional historical blueprint_version hash returned by govern_inference",
"title": "Blueprint Version",
"type": "string"
}
},
"required": [
"api_key",
"inference_id"
],
"title": "get_inference_traceArguments"
}🟢recent_inference_decisions(api_key, limit, action, blueprint, blueprint_version)
Recent generation-governance decisions in this owner's Blueprint version.
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
},
"limit": {
"default": 25,
"description": "Maximum rows to return",
"title": "Limit",
"type": "integer"
},
"action": {
"default": "",
"description": "Optional action filter (STOP, CONTINUE, REVIEW, ...)",
"title": "Action",
"type": "string"
},
"blueprint": {
"default": "default",
"description": "Blueprint namespace used when recording the trace",
"title": "Blueprint",
"type": "string"
},
"blueprint_version": {
"default": "",
"description": "Optional historical blueprint_version hash returned by govern_inference",
"title": "Blueprint Version",
"type": "string"
}
},
"required": [
"api_key"
],
"title": "recent_inference_decisionsArguments"
}🟢verify_certificate(api_key, certificate, data, derivation_rules, formal_constraints)
Independently re-verify a validation certificate. Integrity mode checks the hash chain; full mode (certificate + original data) recomputes every attested rule from scratch - trust nothing, recheck everything.
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
},
"certificate": {
"additionalProperties": true,
"description": "The certificate object from a prior validation response",
"title": "Certificate",
"type": "object"
},
"data": {
"additionalProperties": true,
"default": null,
"description": "Original payload for full re-verification; omit for integrity-only mode",
"title": "Data",
"type": "object"
},
"derivation_rules": {
"default": null,
"description": "Rule list for independent attestation recomputation (optional)",
"items": {},
"title": "Derivation Rules",
"type": "array"
},
"formal_constraints": {
"default": null,
"description": "Optional constraints to match against the committed bundle",
"items": {},
"title": "Formal Constraints",
"type": "array"
}
},
"required": [
"api_key",
"certificate"
],
"title": "verify_certificateArguments"
}🟢profile_blueprint_robustness(api_key, blueprint, config)
Sweep the Blueprint's numeric constraint bounds and report verdict stability: the stable band, the scales where the verdict first flips, and advice. Use before deploying bound changes.
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
},
"blueprint": {
"default": "",
"description": "Blueprint name (workflow_name) to use",
"title": "Blueprint",
"type": "string"
},
"config": {
"additionalProperties": true,
"default": null,
"description": "Raw blueprint config to profile (used when 'blueprint' is not given)",
"title": "Config",
"type": "object"
}
},
"required": [
"api_key"
],
"title": "profile_blueprint_robustnessArguments"
}🟢forecast(api_key, structured_data, blueprint, max_depth, max_branches, ...)
Deterministic forward reasoning: from the current data state, generate and rank the valid next states reachable under the Blueprint's rules.
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
},
"structured_data": {
"additionalProperties": true,
"description": "The document's extracted fields as key/value pairs. Keys are open by design - your Blueprint's rules define what is checked",
"title": "Structured Data",
"type": "object"
},
"blueprint": {
"default": "default",
"description": "Blueprint name (workflow_name) to use",
"title": "Blueprint",
"type": "string"
},
"max_depth": {
"default": 3,
"description": "Search depth, 1-10",
"title": "Max Depth",
"type": "integer"
},
"max_branches": {
"default": 5,
"description": "Branches per step, 1-10",
"title": "Max Branches",
"type": "integer"
},
"rank_by": {
"default": "drift",
"description": "Ranking criterion for returned paths",
"enum": [
"drift",
"confidence",
"shortest",
"risk"
],
"title": "Rank By",
"type": "string"
}
},
"required": [
"api_key",
"structured_data"
],
"title": "forecastArguments"
}⚪discover_patterns(api_key, documents, blueprint)
Learn candidate validation rules and structural document types from a batch of your records, deterministically - no Blueprint required. Promote results with approve_rule. Source data is not stored.
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
},
"documents": {
"description": "List of structured records (objects) to analyze",
"items": {},
"title": "Documents",
"type": "array"
},
"blueprint": {
"default": "default",
"description": "Blueprint name (workflow_name) to use",
"title": "Blueprint",
"type": "string"
}
},
"required": [
"api_key",
"documents"
],
"title": "discover_patternsArguments"
}🟢repair_path(api_key, structured_data, blueprint, max_depth, rank_by)
Find the shortest sequence of field changes taking invalid data to a valid state, as an ordered path of intermediate states. Different from repair (one-shot nearest fix): use repair_path to explain or audit the fix, or compare alternative repairs.
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
},
"structured_data": {
"additionalProperties": true,
"description": "The document's extracted fields as key/value pairs. Keys are open by design - your Blueprint's rules define what is checked",
"title": "Structured Data",
"type": "object"
},
"blueprint": {
"default": "default",
"description": "Blueprint name (workflow_name) to use",
"title": "Blueprint",
"type": "string"
},
"max_depth": {
"default": 4,
"description": "Search depth, 1-10",
"title": "Max Depth",
"type": "integer"
},
"rank_by": {
"default": "shortest",
"description": "Ranking criterion for returned paths",
"enum": [
"shortest",
"drift",
"confidence",
"risk"
],
"title": "Rank By",
"type": "string"
}
},
"required": [
"api_key",
"structured_data"
],
"title": "repair_pathArguments"
}🟢counterfactual(api_key, structured_data, blueprint, rules_b, constraints_b)
Run the same data under two rule sets and compare which future states remain valid - what-if analysis for rule changes.
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
},
"structured_data": {
"additionalProperties": true,
"description": "The document's extracted fields as key/value pairs. Keys are open by design - your Blueprint's rules define what is checked",
"title": "Structured Data",
"type": "object"
},
"blueprint": {
"default": "default",
"description": "Blueprint name (workflow_name) to use",
"title": "Blueprint",
"type": "string"
},
"rules_b": {
"default": null,
"description": "Alternative derivation rules (rule set B)",
"items": {},
"title": "Rules B",
"type": "array"
},
"constraints_b": {
"default": null,
"description": "Alternative constraints (rule set B)",
"items": {},
"title": "Constraints B",
"type": "array"
}
},
"required": [
"api_key",
"structured_data"
],
"title": "counterfactualArguments"
}🟢analyze_anomaly(api_key, structured_data, blueprint)
Explain whether a record fits the usual pattern for records like it, and which fields stand out. No Blueprint required.
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
},
"structured_data": {
"additionalProperties": true,
"description": "The document's extracted fields as key/value pairs. Keys are open by design - your Blueprint's rules define what is checked",
"title": "Structured Data",
"type": "object"
},
"blueprint": {
"default": "default",
"description": "Discovery namespace used by discover_patterns",
"title": "Blueprint",
"type": "string"
}
},
"required": [
"api_key",
"structured_data"
],
"title": "analyze_anomalyArguments"
}🟡create_chain(api_key, blueprint, stages, ttl)
Create a multi-agent sequential chain: stages validate in order against one Blueprint, repairs propagate forward, TTL bounds the run. Siblings: submit_chain_stage advances the chain; handoff_audit verifies a transition between stages. Returns chain_id.
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
},
"blueprint": {
"description": "Blueprint governing all stages of the chain",
"title": "Blueprint",
"type": "string"
},
"stages": {
"description": "Stage definitions, e.g. [{'stage_name':'extract','agent_name':'PDF Agent'}]; minimum 2",
"items": {},
"title": "Stages",
"type": "array"
},
"ttl": {
"default": 3600,
"description": "Chain timeout in seconds; stages cannot advance after expiry",
"title": "Ttl",
"type": "integer"
}
},
"required": [
"api_key",
"blueprint",
"stages"
],
"title": "create_chainArguments"
}🟡submit_chain_stage(api_key, chain_id, stage, structured_data)
Submit data for the chain's current stage; the platform validates it and advances the chain if it passes. Response includes next-stage info and accumulated repairs.
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
},
"chain_id": {
"description": "Chain identifier returned by create_chain",
"title": "Chain Id",
"type": "string"
},
"stage": {
"description": "Stage name to submit for (must be the chain's current stage)",
"title": "Stage",
"type": "string"
},
"structured_data": {
"additionalProperties": true,
"description": "The document's extracted fields as key/value pairs. Keys are open by design - your Blueprint's rules define what is checked",
"title": "Structured Data",
"type": "object"
}
},
"required": [
"api_key",
"chain_id",
"stage",
"structured_data"
],
"title": "submit_chain_stageArguments"
}🟢handoff_audit(api_key, chain_id, from_stage, to_stage, proposed_data)
Audit a handoff between two chain stages: a context capsule of verified facts from the prior stage, and (if proposed_data is given) a compatibility verdict that catches fields mutated in transit. Siblings: create_chain, submit_chain_stage.
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
},
"chain_id": {
"description": "Chain identifier returned by create_chain",
"title": "Chain Id",
"type": "string"
},
"from_stage": {
"description": "Completed stage name (agent A)",
"title": "From Stage",
"type": "string"
},
"to_stage": {
"description": "Stage about to start (agent B)",
"title": "To Stage",
"type": "string"
},
"proposed_data": {
"additionalProperties": true,
"default": null,
"description": "Data agent B intends to submit; checked for mutation against agent A's verified fields",
"title": "Proposed Data",
"type": "object"
}
},
"required": [
"api_key",
"chain_id",
"from_stage",
"to_stage"
],
"title": "handoff_auditArguments"
}⚪approve_rule(api_key, rule_id, blueprint)
Promote a rule discovered by discover_patterns into Blueprint-ready form.
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
},
"rule_id": {
"description": "Discovered rule ID from discover_patterns",
"title": "Rule Id",
"type": "string"
},
"blueprint": {
"default": "default",
"description": "Blueprint name (workflow_name) to use",
"title": "Blueprint",
"type": "string"
}
},
"required": [
"api_key",
"rule_id"
],
"title": "approve_ruleArguments"
}⚪reject_rule(api_key, rule_id, blueprint)
Reject a discovered candidate rule so it will not be promoted into a Blueprint. Pair with approve_rule after discover_patterns.
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
},
"rule_id": {
"description": "Discovered rule ID from discover_patterns",
"title": "Rule Id",
"type": "string"
},
"blueprint": {
"default": "default",
"description": "Blueprint name (workflow_name) to use",
"title": "Blueprint",
"type": "string"
}
},
"required": [
"api_key",
"rule_id"
],
"title": "reject_ruleArguments"
}🟢structural_types(api_key, blueprint)
Retrieve the document categories a discover_patterns session identified (counts, distinguishing fields, domain hints). Read-only; returns status=no_session if discovery has not run for this namespace.
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
},
"blueprint": {
"default": "default",
"description": "Blueprint name (workflow_name) to use",
"title": "Blueprint",
"type": "string"
}
},
"required": [
"api_key"
],
"title": "structural_typesArguments"
}🟢decompose_failure(api_key, original_values, corrected_values, derivation_rules, formal_constraints, ...)
Split the error between original and corrected values into direct rule violations, boundary violations, and systemic structural error, with per-field contributions. Use with a known-correct version to diff against; use analyze_anomaly when you only have the suspicious payload. Diagnostics-tier tool.
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
},
"original_values": {
"additionalProperties": true,
"description": "Original numeric field values as {field: number}",
"title": "Original Values",
"type": "object"
},
"corrected_values": {
"additionalProperties": true,
"description": "Corrected/expected numeric field values as {field: number}",
"title": "Corrected Values",
"type": "object"
},
"derivation_rules": {
"default": null,
"description": "Math rules as objects. Types: add, subtract, multiply, divide, round, copy, sum (multi-operand), items_multiply, items_sum. Each needs 'type' plus its fields; see the blueprint_guide prompt",
"items": {},
"title": "Derivation Rules",
"type": "array"
},
"formal_constraints": {
"default": null,
"description": "Constraint objects. Types incl. magnitude_anchor {field,min,max}, relative_anchor {field,reference_field,ratio_min,ratio_max}, max_action_threshold {field,threshold,on_violation}, required_fields {fields}, equals, range, in_set, regex_match, items_magnitude_anchor; see the blueprint_guide prompt",
"items": {},
"title": "Formal Constraints",
"type": "array"
},
"blueprint": {
"default": null,
"description": "Load rules from this Blueprint instead of passing them inline",
"title": "Blueprint",
"type": "string"
}
},
"required": [
"api_key",
"original_values",
"corrected_values"
],
"title": "decompose_failureArguments"
}🟢geometric_confidence(api_key, state_vector)
Summarize an already-computed state_vector into a confidence level (high/medium/low) with a recommendation. Post-hoc digest - use analyze_anomaly or check_drift for fresh analysis of raw data.
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
},
"state_vector": {
"additionalProperties": true,
"description": "state_vector object from a prior validate or get_execution_trace result",
"title": "State Vector",
"type": "object"
}
},
"required": [
"api_key",
"state_vector"
],
"title": "geometric_confidenceArguments"
}🟢check_realization(api_key, structured_data, blueprint)
Structural realization analysis of a payload against the Blueprint's reference configuration (requires a 'realization' block; otherwise status=skipped). Diagnostics-tier tool; prefer validate or analyze_anomaly for standard checks.
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
},
"structured_data": {
"additionalProperties": true,
"description": "The document's extracted fields as key/value pairs. Keys are open by design - your Blueprint's rules define what is checked",
"title": "Structured Data",
"type": "object"
},
"blueprint": {
"default": "default",
"description": "Blueprint name (workflow_name) to use",
"title": "Blueprint",
"type": "string"
}
},
"required": [
"api_key",
"structured_data"
],
"title": "check_realizationArguments"
}🟢check_drift(api_key, structured_data, blueprint)
Check whether recent submissions still match the established pattern for this Blueprint. Returns a stability verdict and observation count.
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
},
"structured_data": {
"additionalProperties": true,
"description": "The document's extracted fields as key/value pairs. Keys are open by design - your Blueprint's rules define what is checked",
"title": "Structured Data",
"type": "object"
},
"blueprint": {
"default": "default",
"description": "Blueprint name (workflow_name) to use",
"title": "Blueprint",
"type": "string"
}
},
"required": [
"api_key",
"structured_data"
],
"title": "check_driftArguments"
}⚪authorize_execution(api_key, structured_data, blueprint)
Go/no-go for a real-world action (payment, filing, API write): runs full validation, then the Blueprint's execution gate. authorized=true only on PASS; REVIEW means do not proceed automatically. Different from validate: validate asks is this data correct, authorize_execution asks should this action happen.
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
},
"structured_data": {
"additionalProperties": true,
"description": "The document's extracted fields as key/value pairs. Keys are open by design - your Blueprint's rules define what is checked",
"title": "Structured Data",
"type": "object"
},
"blueprint": {
"description": "Blueprint name (workflow_name) to use",
"title": "Blueprint",
"type": "string"
}
},
"required": [
"api_key",
"structured_data",
"blueprint"
],
"title": "authorize_executionArguments"
}🟢load_rule_pack(api_key, pack_id)
Load a prebuilt Blueprint template (invoices, timecards, legal, POs, claims). Call without pack_id to list packs; then create_blueprint to save a customized copy.
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
},
"pack_id": {
"default": null,
"description": "Rule pack ID; omit to list available packs",
"title": "Pack Id",
"type": "string"
}
},
"required": [
"api_key"
],
"title": "load_rule_packArguments"
}🟢get_execution_trace(api_key, structured_data, blueprint)
Run validation and return the per-node execution trace (node names, deterministic flags, timing) plus the verdict and determinism hash. Use validate for normal operation; this is for debugging and audit preparation.
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
},
"structured_data": {
"additionalProperties": true,
"description": "The document's extracted fields as key/value pairs. Keys are open by design - your Blueprint's rules define what is checked",
"title": "Structured Data",
"type": "object"
},
"blueprint": {
"default": "default",
"description": "Blueprint name (workflow_name) to use",
"title": "Blueprint",
"type": "string"
}
},
"required": [
"api_key",
"structured_data"
],
"title": "get_execution_traceArguments"
}🟢verify_replay(api_key, contract_a, contract_b)
Check replay commitment integrity and compare recorded execution components. Version 4 includes reference context and the final result/status. A match compares commitments; this tool does not rerun the workflow or reconstruct historical reference populations, and does not prove factual correctness.
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
},
"contract_a": {
"additionalProperties": true,
"description": "replay_contract object from one execution",
"title": "Contract A",
"type": "object"
},
"contract_b": {
"additionalProperties": true,
"description": "replay_contract object to compare against contract_a",
"title": "Contract B",
"type": "object"
}
},
"required": [
"api_key",
"contract_a",
"contract_b"
],
"title": "verify_replayArguments"
}🟢account_status(api_key)
This account's plan, key usage, Blueprint counts, and the deployed platform build fingerprint (version, build, deployed).
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
}
},
"required": [
"api_key"
],
"title": "account_statusArguments"
}🔴delete_blueprint(api_key, workflow_name, confirm)
Permanently delete a Blueprint and revoke its API keys. Irreversible; requires confirm=true. Account-level keys are unaffected.
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
},
"workflow_name": {
"description": "Blueprint to delete; its API keys are revoked",
"title": "Workflow Name",
"type": "string"
},
"confirm": {
"default": false,
"description": "Must be true to confirm this irreversible action",
"title": "Confirm",
"type": "boolean"
}
},
"required": [
"api_key",
"workflow_name"
],
"title": "delete_blueprintArguments"
}🔴update_blueprint(api_key, workflow_name, customer_name, mode, extracted_fields, ...)
Update an existing Blueprint in place. Only passed fields change; pass [] to clear a list. workflow_name cannot be renamed and existing API keys keep working. Different from create_blueprint: modifies an existing Blueprint, mints no new key.
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
},
"workflow_name": {
"description": "Unique Blueprint identifier; the value passed as 'blueprint' in validate",
"title": "Workflow Name",
"type": "string"
},
"customer_name": {
"default": null,
"description": "Organization or project name (also used for storage folder naming)",
"title": "Customer Name",
"type": "string"
},
"mode": {
"default": null,
"description": "New mode: observe or enforce; omit to keep current",
"title": "Mode",
"type": "string"
},
"extracted_fields": {
"default": null,
"description": "Field names the agent extracts from source data, e.g. ['vendor','qty','unit_cost']",
"items": {},
"title": "Extracted Fields",
"type": "array"
},
"derived_fields": {
"default": null,
"description": "Field names the platform computes from other fields, e.g. ['subtotal','total']",
"items": {},
"title": "Derived Fields",
"type": "array"
},
"derivation_rules": {
"default": null,
"description": "Math rules as objects. Types: add, subtract, multiply, divide, round, copy, sum (multi-operand), items_multiply, items_sum. Each needs 'type' plus its fields; see the blueprint_guide prompt",
"items": {},
"title": "Derivation Rules",
"type": "array"
},
"formal_constraints": {
"default": null,
"description": "Constraint objects. Types incl. magnitude_anchor {field,min,max}, relative_anchor {field,reference_field,ratio_min,ratio_max}, max_action_threshold {field,threshold,on_violation}, required_fields {fields}, equals, range, in_set, regex_match, items_magnitude_anchor; see the blueprint_guide prompt",
"items": {},
"title": "Formal Constraints",
"type": "array"
},
"semantic_checks": {
"default": null,
"description": "Domain-specific semantic check objects",
"items": {},
"title": "Semantic Checks",
"type": "array"
},
"require_math": {
"default": null,
"description": "Validate mathematical relationships",
"title": "Require Math",
"type": "boolean"
},
"require_consistency": {
"default": null,
"description": "Check internal field consistency",
"title": "Require Consistency",
"type": "boolean"
},
"require_coherence": {
"default": null,
"description": "Check cross-field plausibility",
"title": "Require Coherence",
"type": "boolean"
},
"require_provenance": {
"default": null,
"description": "Require extraction source locations for fields",
"title": "Require Provenance",
"type": "boolean"
},
"require_high_assurance": {
"default": null,
"description": "Strictest mode: every check must pass",
"title": "Require High Assurance",
"type": "boolean"
},
"enable_anomaly_detection": {
"default": null,
"description": "Flag records that break no rules but do not fit the reference pattern",
"title": "Enable Anomaly Detection",
"type": "boolean"
},
"enable_drift_tracking": {
"default": null,
"description": "Track pattern stability across batches",
"title": "Enable Drift Tracking",
"type": "boolean"
}
},
"required": [
"api_key",
"workflow_name"
],
"title": "update_blueprintArguments"
}🟢list_api_keys(api_key)
List this account's API keys (masked) with their Blueprint bindings.
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
}
},
"required": [
"api_key"
],
"title": "list_api_keysArguments"
}🔴rotate_api_key(api_key, key_to_rotate)
Replace an API key with a fresh one. The old key stops working immediately; the new key inherits its bindings.
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
},
"key_to_rotate": {
"description": "The gai_ key to rotate; it stops working immediately",
"title": "Key To Rotate",
"type": "string"
}
},
"required": [
"api_key",
"key_to_rotate"
],
"title": "rotate_api_keyArguments"
}🔴delete_api_key(api_key, key_to_delete, confirm)
Permanently delete one of the caller's API keys. DESTRUCTIVE — agents using the deleted key will receive auth errors immediately. The Blueprint a key was tied to (if any) is NOT affected; only the credential is revoked. To delete a Blueprint and all its keys, use delete_blueprint. The target key can be specified two ways: - As the full key string (gai_...). - As a key_id (SHA-256 hash from list_api_keys).
Esquema de entrada
{
"type": "object",
"properties": {
"api_key": {
"description": "GeodesicAI API key (gai_...)",
"title": "Api Key",
"type": "string"
},
"key_to_delete": {
"description": "The gai_ key to delete",
"title": "Key To Delete",
"type": "string"
},
"confirm": {
"default": false,
"description": "Must be true to confirm this irreversible action",
"title": "Confirm",
"type": "boolean"
}
},
"required": [
"api_key",
"key_to_delete"
],
"title": "delete_api_keyArguments"
}Prompts recomendados
get_inference_traceget_inference_tracelist_blueprintslist_blueprintslist_blueprintsget_inference_traceComunidad
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