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recall

Search across local, team, or org scopes and return the best matching knowledge entries. Usage increments a recall counter to improve future relevance.

Instructions

Search knowledge across scopes and return the best matches. THE read endpoint for every agent type — a coding agent, a Slack KB bot, an SRE bot — they all ask here, so knowledge captured once serves them all.

scope : auto (local+team+org, the default) | local | team | org limit : max results

Every returned item's recall counter is incremented (local directly, team best-effort via the shared branch) — usage is the trust signal promotion feeds on. If nothing clears the relevance floor the response says no_confident_match: true — don't present weak matches as established fact.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYes
scopeNoauto

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Even without annotations, the description transparently discloses side effects (recall counter increment, trust signal promotion) and response behavior (no_confident_match flag), providing critical behavioral context for an agent.

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?

Description is front-loaded with purpose and well-structured across a few sentences, though it could be slightly more concise. Still efficient for the information provided.

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

Completeness4/5

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

Covers all key aspects: purpose, parameters, side effects, error behavior. Does not describe output schema, but output schema exists. Nearly complete for a search tool.

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

Parameters5/5

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

With 0% schema description coverage, the description fully compensates by explaining 'scope' values (auto, local, team, org), 'limit' as max results, and defaults, adding essential meaning beyond the raw schema.

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?

Description explicitly states 'Search knowledge across scopes and return the best matches' and identifies it as 'THE read endpoint for every agent type', clearly distinguishing it from sibling tools that are write/management oriented.

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

Usage Guidelines4/5

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

The description clarifies when to use the tool (read/search) by explaining scope options and limit, and implicitly contrasts with siblings like 'capture' or 'endorse'. Could be more explicit about when not to use, but adequate.

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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