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dashclaw_behavior_suggestions

Retrieve evidence-backed policy suggestions learned from agent behavior. Review confidence, sample size, and expected effect before adopting via Policy Coach UI.

Instructions

List DashClaw Policy Coach suggestions — evidence-backed, observe-only policy suggestions the analyzer learned from this agent's locally-recorded behavior (destructive commands, protected-path writes, repeated reloads, failed loops, model/task mismatches, and the safe operating envelope). Read-only: each suggestion carries confidence, sample size, evidence, and expected effect. Review, simulate, and adopt them from the Policy Coach UI — nothing is enforced automatically.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agent_idNoOverride default agent ID (filter to one agent)
Behavior4/5

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

With no annotations, the description fully discloses read-only nature, lists behavioral categories (destructive commands, etc.), and details what each suggestion includes. It adds value beyond what annotations would provide.

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 a single paragraph that front-loads the purpose and provides essential details without unnecessary repetition. It is concise but could be slightly more structured.

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 no output schema, the description explains return fields (confidence, sample size, etc.) and directs users to the UI for further actions. It covers the tool's scope adequately for a listing tool with one optional parameter.

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 coverage is 100%, so the schema already documents the parameter. The description does not add extra meaning beyond the schema's 'Override default agent ID'.

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 starts with a clear verb 'List' and specifies the resource 'DashClaw Policy Coach suggestions'. It elaborates on the nature of suggestions (evidence-backed, observe-only) and lists specific categories, making it distinct from sibling tools like dashclaw_policies_list or dashclaw_guard.

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 states the tool is read-only and intended for reviewing suggestions, not for enforcement, which provides clear usage context. However, it does not explicitly compare with sibling tools or state when to avoid using it.

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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