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MisakaNet

by Ikalus1988
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Python

misakanet_search

Read-onlyIdempotent

Search a public failure-lesson index by error text, keyword, or topic to discover relevant lessons when you do not know a lesson ID. Filter by domain, result type, and detail level.

Instructions

Search MisakaNet's public failure-lesson index by error text, keyword, or topic. Use when you need to discover relevant lessons and do not already know a lesson ID. Input semantics: query is required; domain optionally filters by lesson domain; top limits ranked results and defaults to 5. kind filters by result type: 'lessons' (lesson files only), 'evidence' (results with evidence_refs or verification), 'related' (cross-referenced/tag-overlap), 'all' (default). kind is auto-detected from query intent when omitted (e.g. 'lesson about X' → lessons, 'evidence for X' → evidence). Set explain=true to return matched terms, TF-IDF, entity matches, vector similarity, and hybrid score components. detail controls progressive disclosure: compact (default, ~80 tok/lesson) for broad scans, summary (~200 tok) with domain/tags/fix, full for complete lesson markdown. Output schema: JSON with results[] and source; each result is a ranked lesson summary. Error cases: missing query, unavailable search index, or no matches (empty results). Side effects: none. Auth: none. Rate limits: local stdio process only; callers should keep result counts small. Do not use for private log collection; search only with redacted snippets. Use misakanet_get_lesson for full content.

Input Schema

NameRequiredDescriptionDefault
topNoMaximum ranked results to return. Defaults to 5; keep small for MCP context and latency.
kindNoFilter results by kind: 'lessons' returns only lesson files, 'evidence' returns results with evidence_refs or high evidence_level, 'related' returns cross-referenced/tag-overlap results. Default 'all' returns everything. Auto-detected from query intent when omitted (e.g. 'lesson about X' → lessons, 'evidence for X' → evidence).
queryYesRequired redacted error message, keyword, or topic (for example: 'pip install timeout' or 'DCO sign-off failed').
detailNoProgressive disclosure: compact (default, ~80 tok/lesson) shows id/title/problem/freshness; summary (~200 tok) adds domain/tags/fix; full returns complete lesson markdown. Use compact for broad scans, full only after narrowing results.
domainNoOptional domain filter such as devops, python, network, feishu, rag, fanuc, or mcp.
explainNoInclude score evidence for each result; vector similarity is null when the optional backend is unavailable.
bm25_weightNoOverride BM25 keyword weight (0-1). Higher values favor exact keyword matches. Default: 0.65. All weights must sum to 1.0.
include_staleNoInclude stale and superseded lessons in results. Default false — these are filtered out to avoid误导 agents with outdated information.
baseline_weightNoOverride baseline score weight (0-1). Higher values favor proven/popular lessons. Default: 0.15.
metadata_weightNoOverride metadata bonus weight (0-1). Higher values favor lessons with matching domain/tags. Default: 0.20.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv2.28.0
    • addedInput schema / properties / include_stale
      Added value: +{
+  "description": "Include stale and superseded lessons in results. Default false — these are filtered out to avoid误导 agents with outdated information.",
+  "type": "boolean"
+}
    • addedInput schema / properties / kind
      Added value: +{
+  "description": "Filter results by kind: 'lessons' returns only lesson files, 'evidence' returns results with evidence_refs or high evidence_level, 'related' returns cross-referenced/tag-overlap results. Default 'all' returns everything. Auto-detected from query intent when omitted (e.g. 'lesson about X' → lessons, 'evidence for X' → evidence).",
+  "enum": [
+    "all",
+    "lessons",
+    "evidence",
+    "related"
+  ],
+  "type": "string"
+}
  2. Changed3 schema fields changedv2.23.0
    • addedInput schema / properties / baseline_weight
      Added value: +{
+  "description": "Override baseline score weight (0-1). Higher values favor proven/popular lessons. Default: 0.15.",
+  "type": "number"
+}
    • addedInput schema / properties / bm25_weight
      Added value: +{
+  "description": "Override BM25 keyword weight (0-1). Higher values favor exact keyword matches. Default: 0.65. All weights must sum to 1.0.",
+  "type": "number"
+}
    • addedInput schema / properties / metadata_weight
      Added value: +{
+  "description": "Override metadata bonus weight (0-1). Higher values favor lessons with matching domain/tags. Default: 0.20.",
+  "type": "number"
+}
  3. Changed1 schema field changedv2.21.0
    • addedInput schema / properties / detail
      Added value: +{
+  "description": "Progressive disclosure: compact (default, ~80 tok/lesson) shows id/title/problem/freshness; summary (~200 tok) adds domain/tags/fix; full returns complete lesson markdown. Use compact for broad scans, full only after narrowing results.",
+  "enum": [
+    "compact",
+    "summary",
+    "full"
+  ],
+  "type": "string"
+}
  4. Changed1 schema field changedv2.17.1
    • addedInput schema / properties / explain
      Added value: +{
+  "description": "Include score evidence for each result; vector similarity is null when the optional backend is unavailable.",
+  "type": "boolean"
+}
  5. Changed3 schema fields changedv2.14.0
    • changedInput schema / properties / domain / description
      Previous value: -"Optional domain filter (devops, python, network, feishu, rag, fanuc, etc.)"New value: +"Optional domain filter such as devops, python, network, feishu, rag, fanuc, or mcp."
    • changedInput schema / properties / query / description
      Previous value: -"Search query — error message, keyword, or topic (e.g. 'pip install timeout', 'DCO sign-off failed')"New value: +"Required redacted error message, keyword, or topic (for example: 'pip install timeout' or 'DCO sign-off failed')."
    • changedInput schema / properties / top / description
      Previous value: -"Max results to return (default 5)"New value: +"Maximum ranked results to return. Defaults to 5; keep small for MCP context and latency."
  6. Addedv2.12.4
  7. Removedv2.12.2
  8. First observedv2.12.3

TDQS

A4.4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare read-only, idempotent, open-world, non-destructive, so the safety profile is covered. The description adds real context beyond that: side effects none, auth none, local stdio rate constraint, enumerated error cases, and what explain/staleness do to results. It stops short of describing ranking order or result freshness semantics in depth, so not a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with purpose, then usage, then parameters, then output/errors/side effects — a sensible order. It is somewhat long and the parameter paragraph duplicates schema text, costing a point on economy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 10 parameters, no output schema, and a stateful index, the description covers what results look like (results[] and source, ranked lesson summaries), error behavior, auth, side effects, and rate limits. Everything an agent needs to call this correctly is present.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description's 'Input semantics' paragraph largely restates the schema descriptions for query, domain, top, kind, explain, and detail rather than adding new meaning; the one extra nuance is the omitted-kind auto-detection examples, which the schema also covers.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Search MisakaNet's public failure-lesson index') plus the accepted query forms (error text, keyword, topic). It also distinguishes itself from misakanet_get_lesson, which is named as the tool for full content.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says when to use it ('when you need to discover relevant lessons and do not already know a lesson ID') and when not to ('Do not use for private log collection; search only with redacted snippets'). It names the alternative (misakanet_get_lesson) and the condition that selects it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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