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retrieve_skill

Find agent-readable runbooks that match a task description by semantic similarity. Read-only; returns stored instructions, not execution.

Instructions

Retrieve agent-readable runbooks matching a task description by semantic similarity. Read-only. RecallNest returns stored instructions; it does not execute them.

Input Schema

NameRequiredDescriptionDefault
limitNoMaximum number of matching skills to return, sorted by relevance (default: 3)
queryYesNatural language task description to match, e.g. 'deploy the app to production'
scopeNoRestrict to skills in a specific scope, e.g. 'project:myapp'. Omit to search all scopes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.6.0
  2. Removedv2.5.4
  3. Changed3 schema fields changedv1.0.3
    • changedInput schema / properties / limit / description
      Previous value: -"Max results to return"New value: +"Maximum number of matching skills to return, sorted by relevance (default: 3)"
    • changedInput schema / properties / query / description
      Previous value: -"Task description to match against stored skills"New value: +"Natural language task description to match, e.g. 'deploy the app to production'"
    • changedInput schema / properties / scope / description
      Previous value: -"Optional scope filter"New value: +"Restrict to skills in a specific scope, e.g. 'project:myapp'. Omit to search all scopes"
  4. First observedv1.0.0

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden and does disclose two valuable traits: the operation is read-only and RecallNest returns stored instructions rather than executing them. It says nothing about pagination, scope defaults, or return shape, so the safety profile is covered but operational behavior is not.

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?

Three short sentences, front-loaded with the core retrieval action and its matching mechanism, followed by two tightly scoped disclaimers. Nothing is redundant and no sentence could be removed without losing meaning.

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

Completeness3/5

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

There is no output schema and no annotations, so the description should carry more of the return-value burden — it never indicates what a returned runbook looks like, how many results arrive by default, or what happens on no match. For a simple three-parameter retrieval tool the coverage is minimally adequate but leaves real gaps.

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%, including the query example, the limit default/maximum, and the scope format, so the schema already documents all three parameters. The description adds no syntax, default, or interaction detail beyond it, making the baseline 3 correct.

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

Purpose4/5

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

States a specific verb (Retrieve) and resource (agent-readable runbooks), plus the matching mechanism (semantic similarity by task description). It is clearly distinct in kind from sibling mutations like store_skill or memory_lint, but it never names the closest sibling (e.g. search_memory) to sharpen the contrast.

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

Usage Guidelines3/5

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

The description implies the trigger condition — you supply a natural-language task description and get matching runbooks — but gives no explicit when-to-use versus search_memory, memory_drill_down, or list_assets, and no exclusions or prerequisites. Usage is inferable rather than stated.

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