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skill_fetch

Retrieve skill knowledge for your current task: list matching skills with summaries in plan mode, or fetch a specific skill section body in section mode.

Instructions

Retrieve skill knowledge for the current task. Two modes: 'plan' returns the index (titles, purposes, token estimates) of skills matching your query — read these to decide which sections to fetch; never loads full skill bodies. 'section' fetches ONE section body by (skill_id, section_id) so you pull only the knowledge you need. Default partition is 'working'; 'reference' is opt-in only (held-out skills). Pass runId to pin the exact skill version this run used.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNoplan (Router 1 index) or section (Router 2 body fetch). Default plan.
topKNoplan mode: max skills to return (default 5)
queryNofor plan mode — what you are working on
runIdNooptional — pins the fetched skill version to this run for reproducibility
skill_idNofor section mode — skill to fetch from
partitionNoworking (default, retrievable in normal runs) or reference (held-out, opt-in only)
section_idNofor section mode — one section to return
Behavior5/5

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

With no annotations, the description fully discloses behaviors: plan never loads full bodies, section fetches one section, partition defaults, and runId pins versions. No contradictions.

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 compact (under 100 words) and well-structured: starts with a clear verb+resource statement, then explains modes, parameters, and partitions without redundancy.

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?

Given 7 parameters, two modes, and no output schema, the description covers key behavioral details (modes, partitions, version pinning) but omits the exact structure of returned data for section mode. Still, it is largely complete.

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?

Despite 100% schema coverage, the description adds significant meaning beyond the schema: it explains the two modes, the purpose of each parameter in context (e.g., query for plan, skill_id for section), and default values.

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 explicitly states 'Retrieve skill knowledge for the current task' and distinguishes two modes (plan and section), making the tool's purpose clear and differentiating it from the listed sibling tools.

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?

The description provides explicit guidance on when to use each mode: plan for reading the index to decide which sections to fetch, and section for fetching one section body. It also clarifies default and opt-in partitions.

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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