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capture_feedback

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Capture up/down feedback with a reason to improve agent decisions and execution. Vague entries trigger a clarification prompt for precise learning.

Instructions

Capture an up/down signal plus one line of why. Vague feedback is logged, then returned with a clarification prompt instead of memory promotion.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
signalYes
failureTypeNoDual-signal: "decision" = wrong tool/action chosen, "execution" = right tool but bad parameters/output. Improves Thompson Sampling precision.
contextNoOne-sentence reason describing what worked or failed
relatedFeedbackIdNoOptional prior feedback event to merge with later follow-up context.
whatWentWrongNo
whatToChangeNo
whatWorkedNo
chatHistoryNoOptional caller-supplied recent conversation window used for history-aware lesson distillation. The current Claude auto-capture path sends up to 8 prior recorded entries for vague negative inline signals.
tagsNo
skillNo
conversationWindowNoRecent conversation turns before the feedback signal. Raw messages, not summaries.
rubricScoresNo
guardrailsNo
Behavior1/5

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

Description claims 'Capture' (write operation) contradicts annotations readOnlyHint=true, a serious inconsistency. Does not disclose what side effects occur (e.g., storage, persistence).

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?

Two sentences with no fluff. First sentence states core purpose, second adds key behavioral nuance. Efficient and well-front-loaded.

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

Completeness2/5

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

With 13 parameters, no output schema, and many sibling tools, description is too sparse. Does not explain when to use optional fields, what the return value is, or how different feedback paths work.

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

Parameters2/5

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

Low schema description coverage (38%). Description adds no parameter details; only mentions 'up/down signal' and 'one line of why', which loosely maps to 'signal' and 'context' but not explicitly.

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 it captures an up/down signal and a reason, and distinguishes from memory promotion by mentioning vague feedback handling. Action and resource are specific.

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?

Description implies when to use (precise feedback) and what happens with vague feedback (logged and clarified, not promoted). Lacks explicit alternatives but provides context.

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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