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ModelBound
by ModelBound

skill.report_outcome

Report how a skill performed after you used it. Call this once the task that used the skill is finished — it is how the skill gets improved. Keep excerpts short. Requires MODELBOUND_API_KEY.

Instructions

Report how a skill performed after you used it. Call this once the task that used the skill is finished — it is how the skill gets improved. Keep excerpts short. Requires MODELBOUND_API_KEY.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteNoOne sentence on what happened.
verdictYes
categoryNoOnly when the verdict is not 'worked'.
skill_idYesThe Skill UUID you loaded.
output_excerptNoOptional short excerpt of the bad output.
prompt_excerptNoOptional short excerpt of the task prompt.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.9.0

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It usefully discloses the auth requirement ('Requires MODELBOUND_API_KEY') and the downstream effect ('it is how the skill gets improved'), plus an excerpt-length constraint, but says nothing about where the report goes, whether it is reviewed, or whether it can be revised after submission.

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?

Three short sentences, front-loaded with purpose and trigger, each carrying a distinct piece of information. No filler, though it is quite terse given the operation's importance.

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 feedback-reporting tool with a fully self-documenting schema and no output schema, the description covers purpose, timing, and the one environmental prerequisite. Missing only return/confirmation behavior, which is minor here.

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 83%, so the schema already documents the parameters and enums. The description only adds the 'keep excerpts short' guidance for output_excerpt/prompt_excerpt, adding marginal value beyond the schema, which makes the baseline 3 appropriate.

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?

States a specific verb and resource ('Report how a skill performed') and ties it to the post-task moment. The purpose is unambiguous, though it does not explicitly distinguish itself from the near-named sibling report_run or skill.findings.

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?

Gives clear timing context ('Call this once the task that used the skill is finished'), which is the key trigger for invocation. It provides no explicit exclusions or named alternatives, so it stops short of a 5.

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