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ecoclaw

ecoclaw-mcp

Official
by ecoclaw

tune_skill

Apply plain-language feedback to permanently modify a skill's behavior. Customize instructions locally, preserving the original version.

Instructions

Apply plain-language feedback to a skill, permanently modifying how it works for you. This is the homomorphic heart — your feedback gets written into the skill's prompt and saved locally. The original npm version is never touched. Examples: 'always use a more casual tone', 'end every output with a P.S.', 'never mention competitors'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesSkill name to tune
feedbackYesPlain-language description of how you want the skill to change

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.3/5.0
Behavior5/5

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

With no annotations, the description carries full burden of behavioral disclosure. It openly states that feedback is written into the skill's prompt, saved locally, and that the original npm version is untouched. This gives the agent a clear picture of side effects and persistence, beyond the bare action.

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 concise and front-loaded with the main purpose. However, the phrase 'This is the homomorphic heart' is esoteric and adds no clarity, slightly detracting from the overall structure. It could be removed without loss of information.

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 the simplicity (2 parameters, no output schema), the description covers the essential behavior and side effects. It explains persistence and non-modification of the original. It does not mention error conditions (e.g., skill not found) but that is likely implied. Overall, it is sufficient for an agent to call correctly.

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 baseline is 3. The description adds examples of feedback but does not add meaning beyond the schema's parameter descriptions. The examples are helpful but not essential for understanding the parameters.

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 uses a specific verb ('Apply'), resource ('skill'), and explicitly states the effect ('permanently modifying how it works for you'). It clearly distinguishes from siblings like run_skill and fork_skill by emphasizing the permanent, local modification. The examples further clarify the purpose.

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 implies when to use the tool (to apply feedback to a skill) but does not explicitly contrast with alternatives such as fork_skill or run_skill. It provides clear context ('permanently modifying') but lacks explicit exclusions or a mention of when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.