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observe

Log a behavioral pattern to build agent memory. Each observation raises confidence, turning patterns into rules.

Instructions

Record one observation of a behavioral pattern; increments its confidence counter.

    Use this to log anything you want the agent to learn over time: a tool
    sequence that worked, a user preference, a recurring fix, or a combo
    of tools used together. Call once per occurrence — repeated calls on
    the same pattern raise its confidence (1=new, 5=mature, 10=rule).

    Do NOT use this for one-off notes; those belong in regular memory.
    This tool is for patterns that may recur and become reliable.

    Idempotent on pattern key: same pattern string merges into one entry.

    Args:
        pattern: Pattern key following the convention prefix:body.
            Examples: "seq:lint->fix->lint" (tool sequence),
            "pref:style=black" (user preference),
            "fix:missing-import" (recurring fix),
            "combo:pytest+coverage" (things used together).
        category: Pattern type. One of: "sequence", "preference",
            "fix_pattern", "combo". Defaults to "sequence".
        source: Originating tool/agent name (e.g. "claude-code",
            "cursor"). Empty string means unknown. Useful for filtering.
        project: Project fingerprint. Empty string auto-detects from cwd
            (recommended). Pass explicitly only for cross-project imports.
        explain: One-line human-readable rationale for why this pattern
            matters. Surfaces in suggestions and CLAUDE.md exports.

    Returns:
        Dict with keys: "pattern", "confidence" (int), "level"
        ("seedling" | "mature" | "rule"), "created" (bool — true on
        first observation).
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
patternYes
categoryNosequence
sourceNo
projectNo
explainNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

No annotations provided, but description fully discloses behavioral traits: idempotent on pattern key, confidence levels (1=new, 5=mature, 10=rule), return values. It adds context beyond what structured fields could convey.

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?

Well-structured with sections for purpose, usage, args, returns. Each sentence adds value. Slightly verbose but front-loaded and clear. Could tighten a few phrases without loss.

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

Completeness5/5

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

Given no annotations, complex behavior, 5 parameters, and output schema, description is very complete. Covers when to use, parameter details, idempotency, return values, and conventions. Output schema exists but description explains return dict structure.

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?

Schema description coverage is 0%, but description explains each parameter with examples and conventions (e.g., pattern key format, category default, source and project usage). Adds significant meaning beyond bare schema properties.

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 clearly states the tool records an observation of a behavioral pattern and increments confidence. It distinguishes from siblings by specifying it is for patterns that may recur, not one-off notes, and uses specific verbs like 'record' and 'log'.

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?

Explicitly says when to use (log anything for agent learning) and when not to (one-off notes belong in regular memory). Provides guidance on repeated calls to raise confidence and contrasts with sibling tools like `alias_pattern` or `consolidate`.

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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