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fitz2882

learned-experience

by fitz2882

Record an experience

record

Store what happened after solving or failing a non-trivial problem—fixes, attempts, root causes—so future agents can apply solutions and avoid repeating mistakes.

Instructions

Store what happened after solving (or failing to solve) a non-trivial problem. Duplicates are merged automatically: the response says whether the record was created, merged into an existing one, or linked to one with a different fix. Keep it terse and never include secrets.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fixNoWhat finally worked, concrete enough to repeat. Omit if unresolved.
kindNo'episode' (default) or 'rule' for a generalisation of several episodes
avoidNoWhat did not work or made things worse
sourceNoProvenance: which agent/model is recording
contextNoTags: language, framework, tool, OS, domain. e.g. ['node','postgres','macos']
outcomeYes
problemYesOne-line statement of the problem, as generic as is accurate
signalsNoExact error messages, failing commands, or symptoms. These form the deterministic fingerprint.
attemptsNoOrdered attempts and whether each worked
root_causeNoWhy it happened, if known
Install Server

TDQS

A4.1/5.0
Behavior5/5

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

The description adds meaningful behavioral context beyond the annotations: duplicates are merged automatically, the response indicates whether the record was created, merged, or linked to a different fix, and secrets must never be included. This is valuable operational detail that the schema and annotations do not provide.

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?

The description is compact and front-loaded: it states the core purpose first, then deduplication behavior, then a privacy rule. Every sentence earns its place and nothing is redundant with the schema.

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?

For a tool with 10 parameters and no output schema, the description does a good job covering purpose, when to use it, deduplication behavior, and response semantics. It could be more complete by hinting at how records relate to sibling operations like reinforce or consolidate, but the schema carries the parameter details.

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 description coverage is 90%, so the schema already documents nearly all parameter meanings. The description adds little parameter-level detail, only a stylistic instruction to keep records terse, which does not materially enhance understanding of the 10 parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states a specific action and resource: 'Store what happened after solving (or failing to solve) a non-trivial problem.' This makes the tool's purpose obvious and separates it from read/delete/update siblings like recall, forget, and amend, though it does not explicitly name any alternative.

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 gives clear conditions for use: record after solving or failing to solve a non-trivial problem. It does not explicitly discuss when not to use the tool or point to alternatives, but the when-to-use context is strong enough to guide an agent.

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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