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Report a Bug or Wish

lab_feedback
Idempotent

Tell the FilmLab team about a bug or a missing feature — it reaches the people who can fix it, the chat does not. Use art 'fehler' when a tool returned something wrong, failed without a clear reason, or contradicted its own description; 'wunsch' when a step you needed does not exist. Write what you called, what you expected and what came back; put ids, arguments and the error text into kontext (no secrets, no personal data of third parties). One report per problem. Do not report a refused request that was correct (e.g. 'Project not found' for someone else's project). Needs an account. Free.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
artYesfehler = something is broken; wunsch = something is missing
textYesWhat you called, what you expected, what happened — in a few sentences
titelYesOne line, e.g. 'lab_capture: black frame for an image clip'
kontextNoMachine-readable details: ids, arguments, error text. Max ~8000 characters as JSON
werkzeugNoThe tool it is about, e.g. 'lab_timeline_apply'
project_idNoYour project it happened in (only your own projects are accepted)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / additionalProperties
      Added value: +false
  2. Added

TDQS

A4.5/5.0
Behavior4/5

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

Annotations mark this as a non-read-only but non-destructive, idempotent write, and the description adds real context beyond that: it requires an account, it is free, it forbids secrets/third-party personal data, and 'one report per problem' is consistent with the idempotentHint. It does not say what happens after submission (confirmation, ticket reference), which is the only remaining gap.

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?

Front-loaded with the purpose, then ordered operational instructions; nearly every clause carries a rule the agent needs. Slight overlap with the schema ('what you called, what you expected and what came back' restates the 'text' description), which keeps it from being perfectly tight.

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 single-shot report tool with no output schema, the description covers the account prerequisite, privacy constraints, deduplication rule and anti-misuse exclusion. Only the post-submission outcome (whether a ticket id or receipt is returned) is left unstated, which is minor given there is no output schema to document it.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline would be 3, but the description adds genuine semantics: which 'art' value maps to which real-world situation, that 'kontext' should carry ids, arguments and error text, that 'text' should say what was called/expected/returned, and that only the caller's own project_id is accepted. That is meaningfully more than the enum labels alone.

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?

States a specific verb and resource: 'Tell the FilmLab team about a bug or a missing feature', and immediately distinguishes itself from the in-chat alternative ('the chat does not'). An agent can identify this as the out-of-band escalation channel without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit selection logic between the two enum modes ('fehler' when a tool returned something wrong/failed/contradicted its description; 'wunsch' when a needed step does not exist), plus an explicit exclusion ('Do not report a refused request that was correct') and volume guidance ('one report per problem'). Both when-to-use and when-not-to-use are covered.

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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