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suggest

Retrieve mature, validated patterns from past work to guide current tasks. Filters by project, category, or keyword return high-confidence suggestions sorted by trust.

Instructions

Retrieve mature patterns (confidence >= 5) to guide your current behavior.

    Call this at the start of a task to learn how similar work has been
    handled before: which tool sequences worked, what the user prefers,
    which fixes recur. Results are sorted by confidence descending, so
    the most-trusted patterns come first.

    Prefer this over list_instincts when you want only validated patterns
    (not every observation). Use list_instincts to see seedlings too.

    Args:
        project: Filter by project fingerprint. Empty string returns the
            current project's patterns plus global ones. Pass a specific
            fingerprint to audit another project.
        category: Filter by pattern type. One of: "sequence", "preference",
            "fix_pattern", "combo". Empty string returns all categories.
        keyword: Substring match against pattern key, metadata, and
            explain text. Case-insensitive. Empty string disables filter.
        compact: True (default) returns ~50 tokens per pattern (key +
            confidence + level only) — ideal for agent context. False
            returns full metadata and explain text (~500 tokens each) —
            use for audits or UI display.

    Returns:
        Dict with keys: "suggestions" (list of patterns, compact or
        full depending on flag), "count" (int), and in compact mode a
        "hint" pointing to get_instinct for details.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectNo
categoryNo
keywordNo
compactNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

Description reveals sorting order (by confidence descending), filtering behavior (empty strings return all), defaults, and return structure. With no annotations, it fully discloses behavioral traits, including the hint pointing to get_instinct for details.

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 usage, args, and returns. Slightly lengthy but every sentence adds value. Could be more concise, but still effective.

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 4 parameters, no annotations, and an output schema, the description fully covers input/output behavior, usage context, and distinguishes from a key sibling. Sufficient for an agent to use correctly.

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?

All four parameters are explained with semantics beyond the schema (which lacks descriptions). 'project' handling of empty string, 'category' enum values, 'keyword' substring matching, and 'compact' token counts are all detailed.

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 verb 'Retrieve' and resource 'mature patterns (confidence >= 5)' and distinguishes itself from sibling 'list_instincts' by noting it returns only validated patterns, not seedlings.

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 advises when to call ('at the start of a task'), what to expect ('learn how similar work has been handled before'), and when to prefer alternatives ('Prefer this over list_instincts... use list_instincts to see seedlings'). Also clarifies compact vs full modes.

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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