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store_skill

Persist reusable agent runbooks with trigger conditions, instructions, and verification steps for cross-session retrieval.

Instructions

Store an agent-readable skill runbook with trigger conditions, instruction content, and verification steps. Side effect: persists a new skill entry and indexes it. Use when you identify a reusable procedure worth surfacing across sessions. NOTE: RecallNest does NOT execute skills — implementation is a runbook agents read as context, not a script we run. (v2.5 收缩,2026-05-27)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesUnique skill identifier, e.g. 'deploy_production' or 'run_migrations'
tagsNoOptional categorization tags, e.g. ['deployment', 'production']
scopeYesScope to store the skill under, e.g. 'project:recallnest'
sourceNoHow this skill was captured: 'manual' by user, 'agent' by AI, or 'api' programmaticallyagent
descriptionYesNatural language description of what the skill does (used for semantic retrieval matching)
inputSchemaNoJSON Schema defining the skill's input parameters, e.g. {"env": {"type": "string"}}
verificationNoSteps to verify the skill executed correctly, e.g. 'check deployment URL returns 200'
implementationYesAgent-readable runbook content: markdown steps, natural language workflow, or structured procedure. RecallNest does NOT execute this — agents read it as context to follow.
triggerPatternYesNatural language pattern describing when to suggest this skill, e.g. 'user asks to deploy to production'
implementationTypeYesSkill runbook type. Currently only 'instruction_sequence' is supported — RecallNest stores runbooks for agents to read, does not execute them. (v2.5 schema 收缩,2026-05-27)
Behavior4/5

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

With no annotations, the description carries the full burden. It explicitly discloses the side effect ('persists a new skill entry and indexes it') and the critical non-execution behavior (RecallNest does NOT execute skills). This addresses common misconceptions and provides useful behavioral context beyond a simple 'store' action.

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?

The description is front-loaded with the primary action, followed by side effect, usage, and a crucial warning. It is concise and readable, though the trailing version note '(v2.5 收缩,2026-05-27)' is extraneous for an agent.

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?

The tool has 10 parameters and no output schema, but the schema covers all parameters comprehensively. The description adds usage context, side effects, and a non-execution warning, making the overall tool context sufficiently complete for an agent to use it correctly. Some details like duplicate handling or return value are absent, but not critical for a store operation.

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 the baseline is 3. The description echoes the non-execution note already present in the implementation parameter schema, but does not add new parameter semantics beyond what the schema provides.

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?

The description clearly states the tool stores an 'agent-readable skill runbook' with trigger conditions, instruction content, and verification steps. This specifies the resource and purpose, but does not explicitly distinguish from sibling tools like store_workflow_pattern or store_case, so it falls short of a 5.

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 includes a clear usage context: 'Use when you identify a reusable procedure worth surfacing across sessions.' It does not mention exclusions or direct alternatives, but the provided context is sufficient for an agent to decide when to invoke this tool.

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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