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agent-reasoning-mcp

by putervision
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query_knowledge

Read-onlyIdempotent

Searches learned heuristics, anti-patterns, tactics, and similar past situations by contextual relevance so AI agents can reuse proven guidance during planning and replanning.

Instructions

Search learned heuristic patterns, tactics, and past decision traces by context similarity (actions: search, patterns, similar_situations). Use query_knowledge instead of get_decision_trace when retrieving generalized patterns across sessions rather than inspecting a single execution trace.

Returns matching heuristics, anti-patterns, tactics, and similarity scores.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax patterns to return
queryNoSemantic search query string
actionYesKnowledge query mode: search, patterns, similar_situations
projectNoTarget project slug
context_tagsNoFilter by context tags
pattern_typeNoFilter by pattern category

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.3.1
    • changedInput schema / properties / action / description
      Previous value: -"Knowledge query mode"New value: +"Knowledge query mode: search, patterns, similar_situations"
    • addedInput schema / properties / action / enum
      Added value: +[
+  "search",
+  "patterns",
+  "similar_situations"
+]
  2. Changed9 schema fields changedv0.2.1
    • removedInput schema / $schema
      Removed value: -"http://json-schema.org/draft-07/schema#"
    • removedInput schema / additionalProperties
      Removed value: -false
    • addedInput schema / properties / action / description
      Added value: +"Knowledge query mode"
    • removedInput schema / properties / action / enum
      Removed value: -[
-  "search",
-  "patterns",
-  "similar_situations"
-]
    • addedInput schema / properties / context_tags / description
      Added value: +"Filter by context tags"
    • addedInput schema / properties / limit / description
      Added value: +"Max patterns to return"
    • addedInput schema / properties / pattern_type / description
      Added value: +"Filter by pattern category"
    • addedInput schema / properties / project / description
      Added value: +"Target project slug"
    • addedInput schema / properties / query / description
      Added value: +"Semantic search query string"
  3. First observedv0.1.2

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, non-destructive, and closed-world behavior. The description adds useful return context by naming the kinds of matches returned (heuristics, anti-patterns, tactics, similarity scores) and the cross-session scope, though it does not discuss pagination or rate limits.

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

Conciseness5/5

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

The description is front-loaded with purpose and routing guidance, then states the return contents. Every sentence adds useful information without repetition or filler.

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?

For a six-parameter read-only search tool with rich annotations, the description supplies purpose, usage routing, supported action modes, and the shape of returned results. With no output schema, the return summary is especially valuable and sufficient for correct invocation.

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 description coverage is 100%, so all six parameters are already documented in the schema, including the action and pattern_type enums. The description repeats the action modes but adds no syntax, format, or interaction details beyond what the schema provides.

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?

The description states a specific verb (Search) and resources (learned heuristic patterns, tactics, past decision traces) and names the supported actions. It also explicitly distinguishes the tool from get_decision_trace by contrasting generalized cross-session patterns with a single execution trace.

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?

It gives explicit routing guidance: use query_knowledge instead of get_decision_trace when retrieving generalized patterns across sessions, rather than inspecting one execution trace. This covers when to use it, when to prefer an alternative, and the alternative itself.

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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