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Tell Arcmira what went wrong

arcmira_feedback

Saves a feedback record for the Arcmira team about what was wrong, slow, missing or confusing in a task. Send one when a result was empty, an error, truncated or an ask that did not serve the user, or when the user says something was off. Each call adds a record; repeated calls create separate records. Costs nothing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteYesWhat happened in a sentence or two: what the user asked, what came back, what they expected. No credentials or personal details.
intentNoOptional: the user's request in a few words. Logged with this call to improve Arcmira.
call_idNoThe call_id a result named (mcpc_ followed by 32 hex characters), for the call this is about.
categoryYeswrong_entity: the wrong person, company or show. bad_data: a wrong count, date, quote or label. missing: something that should be there is not. slow: it took too long. confusing: a result, error or rule was hard to act on. other.
request_idNoThe request_id of the error this is about, when there was one.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Adds real context beyond the annotations: 'Each call adds a record; repeated calls create separate records' concretely explains the non-idempotent, append-only behavior flagged by idempotentHint=false, and 'Costs nothing' removes cost as a hesitation. It stays silent on auth requirements and any rate limits, so it is good but not exhaustive.

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?

Three tight sentences with zero filler; the purpose is front-loaded, followed by triggers, then the append/cost caveats. Every sentence carries distinct information an agent needs.

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 5-param, 2-required write tool with no output schema, the description covers purpose, trigger conditions, append semantics, and cost. It does not say what a successful call returns or whether any permission is needed, which are minor remaining gaps.

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 100% and the enum values are fully documented in the schema itself, so the baseline of 3 applies. The description's trigger phrases loosely echo the category options but add no syntax, format, or edge-case detail beyond what the schema already provides.

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 (saves) and resource (a feedback record for the Arcmira team) with the subject matter scoped to what went wrong. This is unmistakably distinct from the sibling execute_read/execute_write/describe tools, which an agent can tell apart without opening any schema.

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 concrete triggering conditions: empty result, error, truncated output, an ask that did not serve the user, or the user saying something was off. Strong when-to-use guidance, but there is no when-not guidance and no explicit reference to an alternative channel for non-feedback problems.

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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