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store_skill

Capture and store reusable automation skills with trigger patterns, implementation scripts, and verification checks for execution across multiple sessions.

Instructions

Store an executable skill with trigger conditions, implementation, and verification steps. Side effect: persists a new skill entry and indexes it. Use when you identify a reusable procedure worth automating across sessions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesUnique skill identifier, e.g. 'deploy_production' or 'run_migrations'
descriptionYesNatural language description of what the skill does (used for semantic retrieval matching)
triggerPatternYesNatural language pattern describing when to suggest this skill, e.g. 'user asks to deploy to production'
implementationTypeYesExecution type: 'bash' for shell scripts, 'python' for Python code, 'mcp_tool_chain' for MCP sequences, 'instruction_sequence' for step-by-step instructions
implementationYesExecutable content: the actual script, code, or instruction steps to run
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'
scopeYesScope to store the skill under, e.g. 'project:recallnest'
sourceNoHow this skill was captured: 'manual' by user, 'agent' by AI, or 'api' programmaticallyagent
tagsNoOptional categorization tags, e.g. ['deployment', 'production']
Behavior3/5

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

Since no annotations are provided, the description carries the full burden. It successfully discloses the mutation side effects ('persists a new skill entry and indexes it'), confirming this is a write operation. However, it omits critical behavioral details like idempotency (behavior on duplicate names), conflict resolution, or return value structure.

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 sentences with zero waste: first defines the action and components, second discloses side effects, third provides usage context. Information is front-loaded with the core operation and efficiently structured.

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?

Given the tool's complexity (10 parameters including nested objects and enums) and lack of annotations/output schema, the description adequately covers the conceptual model but has gaps regarding operational behaviors like error conditions, name collision handling, or the indexing mechanism mentioned.

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

Parameters4/5

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

While the schema has 100% coverage (baseline 3), the description adds conceptual value by grouping parameters into logical categories (trigger conditions, implementation, verification steps) that help the agent understand the relationship between 'triggerPattern', 'implementation', and 'verification' fields beyond their individual schema definitions.

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 clearly states the specific action (Store) and resource (executable skill) with constituent components (trigger conditions, implementation, verification steps). It effectively distinguishes from siblings like 'store_memory' (general memories) and 'store_case' (cases) by emphasizing the 'executable' nature and automation focus.

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?

Provides explicit positive guidance ('Use when you identify a reusable procedure worth automating across sessions'). However, it lacks explicit negative constraints or comparison with alternatives like 'auto_capture' (for automatic capture) or 'store_workflow_pattern' (for patterns vs. executable skills).

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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