doom
Obsolescence-risk screening: predicts if a product gets absorbed into core LLM-platform features.
Sollte ich dies verwenden
Qualität und Sicherheit
Basierend auf einer automatisierten Analyse der Tool-Definitionen und der Einhaltung des Protokolls.
Kontextkosten
Dies ist die ungefähre Anzahl der Tokens, die jedes Mal verbraucht werden, wenn die Tools des Servers in den Kontext eines Modells geladen werden. Höhere Werte verringern die Aufmerksamkeit, die für andere Aufgaben verfügbar ist.
Installieren
Installation mit einem Klick
Fügen Sie dies Ihrer Datei `claude_desktop_config.json` hinzu:
{
"mcpServers": {
"doom": {
"url": "https://mcp.doomscore.vc"
}
}
}Remote-Endpunkte
https://mcp.doomscore.vcstreamable-httpWas es kann
Tool-Inventar
Tools (11)
⚪doom_prep
Prep Gate. Validates config + confirms the roadmap-signals KB is within the staleness threshold. Fails closed if stale. Call before assess_product.
Eingabe-Schema
{
"type": "object",
"properties": {},
"additionalProperties": false
}🟢assess_product(description, url, pitch_company_id, deck_text, mode, ...)
Assess one product's obsolescence risk. Provide exactly ONE of description/url/pitch_company_id/deck_text. Async — returns job_id; poll get_assessment. Defaults to deep mode. Optionally pass requested_by to identify the caller (shown in the activity feed).
Eingabe-Schema
{
"type": "object",
"properties": {
"description": {
"type": "string"
},
"url": {
"type": "string"
},
"pitch_company_id": {
"type": "string"
},
"deck_text": {
"type": "string"
},
"mode": {
"type": "string",
"enum": [
"quick",
"deep"
],
"default": "deep"
},
"requested_by": {
"type": "string",
"description": "Who is requesting this assessment (name/handle/agent id) — shown in the #doom-activity feed; defaults to anonymous."
}
},
"additionalProperties": false
}🟢get_assessment(job_id)
Poll an assessment job_id. Returns status + the typed assessment when complete. Hard timeout — never hangs on pending.
Eingabe-Schema
{
"type": "object",
"properties": {
"job_id": {
"type": "string"
}
},
"required": [
"job_id"
],
"additionalProperties": false
}🟢list_assessments(verdict, limit)
Recent assessments, filterable by verdict.
Eingabe-Schema
{
"type": "object",
"properties": {
"verdict": {
"type": "string"
},
"limit": {
"type": "number",
"default": 20
}
},
"additionalProperties": false
}⚪overview
Inspectable State. No input. Counts, recent activity, roadmap-signal freshness, health, last calibration run.
Eingabe-Schema
{
"type": "object",
"properties": {},
"additionalProperties": false
}⚪record_outcome(operator_key, job_id, product, actual_outcome, expected_verdict, ...)
Outcome-feedback (learning loop). Record what ACTUALLY happened to a previously-assessed product as a labeled calibration case; the weekly recalibration folds it into the gate. Operator-only (requires operator_key). Provide either job_id (links the case to that assessment + reuses its product) or product text.
Eingabe-Schema
{
"type": "object",
"properties": {
"operator_key": {
"type": "string"
},
"job_id": {
"type": "string"
},
"product": {
"type": "string"
},
"actual_outcome": {
"type": "string",
"enum": [
"sherlocked",
"survived",
"thrived"
]
},
"expected_verdict": {
"type": "string",
"enum": [
"roadkill",
"squeezed",
"defensible",
"riding-the-wave"
]
},
"year_observed": {
"type": "number"
},
"notes": {
"type": "string"
}
},
"required": [
"operator_key",
"actual_outcome",
"expected_verdict"
],
"additionalProperties": false
}🟢list_signal_candidates(operator_key, status, limit)
KB-refresh review queue. List auto-scraped candidate roadmap signals (default: pending). Operator-only. Approve/reject with review_signal_candidate; the weekly cron signs approved ones into the live KB.
Eingabe-Schema
{
"type": "object",
"properties": {
"operator_key": {
"type": "string"
},
"status": {
"type": "string",
"enum": [
"pending",
"approved",
"rejected",
"signed"
]
},
"limit": {
"type": "number",
"default": 50
}
},
"required": [
"operator_key"
],
"additionalProperties": false
}⚪review_signal_candidate(operator_key, candidate_id, action)
Approve or reject a KB-refresh candidate signal. Operator-only. Approved candidates are signed (Ed25519) into the live roadmap_signals KB by the next refresh run; rejected ones are dropped. Controls what becomes grounding truth.
Eingabe-Schema
{
"type": "object",
"properties": {
"operator_key": {
"type": "string"
},
"candidate_id": {
"type": "string"
},
"action": {
"type": "string",
"enum": [
"approve",
"reject"
]
}
},
"required": [
"operator_key",
"candidate_id",
"action"
],
"additionalProperties": false
}🟢list_kb_signals(operator_key)
List the active (signed, grounding) roadmap signals with their ids — use to find a signal_id to retire. Operator-only.
Eingabe-Schema
{
"type": "object",
"properties": {
"operator_key": {
"type": "string"
}
},
"required": [
"operator_key"
],
"additionalProperties": false
}🟢retire_signal(operator_key, signal_id, reason)
UNLEARN a KB signal that became false/obsolete (e.g. a rumored feature cancelled, or a signal no longer predictive). Soft-deletes it (active=false) so it stops grounding assessments immediately — recoverable. Operator-only. Find the id via list_kb_signals.
Eingabe-Schema
{
"type": "object",
"properties": {
"operator_key": {
"type": "string"
},
"signal_id": {
"type": "string"
},
"reason": {
"type": "string"
}
},
"required": [
"operator_key",
"signal_id",
"reason"
],
"additionalProperties": false
}⚪supersede_calibration_case(operator_key, case_id, reason)
UNLEARN a calibration case whose label turned out wrong or obsolete — retires it (active=false) so the recalibration gate stops scoring it. To correct, retire the wrong case then record_outcome the right one. Operator-only.
Eingabe-Schema
{
"type": "object",
"properties": {
"operator_key": {
"type": "string"
},
"case_id": {
"type": "string"
},
"reason": {
"type": "string"
}
},
"required": [
"operator_key",
"case_id",
"reason"
],
"additionalProperties": false
}Empfohlene Prompts
get_assessmentget_assessmentlist_assessmentslist_assessmentslist_assessmentsget_assessmentCommunity
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