Skip to main content
Glama
rodlunt

engineering-audit

by rodlunt

submit_feedback

Submit optional run feedback to the engineering-audit tool author, with consented telemetry, as a GitHub issue or mailto fallback.

Instructions

Send optional run feedback to the tool author.

    Requires a resolved configuration. There is nothing to send unless
    config.feedback_text was set on the configuration page, or the
    calling agent supplies extra_text; if neither is present this
    raises rather than filing an empty, pointless issue.

    The feedback body always carries the free text plus a run-metadata
    section (tool version, rules pack, assistant, model, repository,
    timestamps), and then each telemetry section the user consented to
    on the configuration page (coverage totals, findings rollup by
    severity/domain id, self-assessment, environment, consulted sources
    by rule id/url/why, rule verdict distribution by domain and in
    total, run duration and the divergence verdict between its two
    measurements, which domains had their rule text fetched via
    get_domain, and the reader's own conclusions after reading the
    report); an unconsented section is left out entirely. Finding text
    itself is never included, only counts.

    report_conclusion and report_fix_first (issue #135) are the
    reader's own answers, in their own words, to the two questions the
    finished report's own feedback form asks: in one sentence, what did
    this report tell them about their repository, and what would they
    fix first. Pass these only if the human using this session actually
    read the finished report and dictated an answer back; never guess
    or paraphrase one on their behalf. Both are ignored unless the
    reader_conclusions section was consented to on the configuration
    page, same as every other telemetry section here.

    Files a labelled issue on the tool author's feedback repository via
    gh. If gh is unavailable or filing fails for any reason, the
    feedback is never lost: this returns a mailto fallback instead,
    with the same body, so the agent can offer to open the user's mail
    client or hand over the text to paste in manually.

    May be called either before or after render_report. Called after,
    it sends feedback for the run just finished and rewrites that run's
    report.html and run-state.json so both carry the feedback issue's
    link; the response's report_updated field says whether that rewrite
    succeeded, and a failed rewrite is reported as a warning rather than
    an error, because the issue is already filed by then and raising
    would invite a retry that double-files it.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
extra_textNo
report_fix_firstNo
report_conclusionNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

With no annotations, the description fully carries the transparency burden and delivers extensively. It discloses failure behavior (raises when nothing to send, mailto fallback on gh failure), consent-based telemetry inclusion, rewriting of report.html/run-state.json, and the deliberate warning rather than error after a failed rewrite to avoid double-filing.

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 information-dense and front-loaded with a clear first sentence, but the telemetry section list is an extremely long parenthetical that hurts readability. All content earns its place, yet tightening the structure would improve conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having an output schema, the description covers all critical operational context: preconditions, content construction, parameter ethics, failure modes, timing relative to render_report, side effects, and idempotency concerns. This level of detail is necessary for correct invocation and retry behavior.

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

Parameters5/5

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

Schema coverage is 0%, but the description compensates thoroughly. It explains extra_text as agent-supplied free text, and provides extensive semantic and ethical guidance for report_conclusion and report_fix_first, including when they are ignored and that they must be the human's own words.

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 opening sentence, 'Send optional run feedback to the tool author,' identifies a specific verb, resource, and audience, clearly distinguishing this from sibling tools like file_issues and render_report. Additional details about filing a labeled issue on the author's feedback repository reinforce the tool's unique role.

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 provides clear usage context: it requires a resolved configuration, only sends if config.feedback_text or extra_text is present, and may be called before or after render_report with different behaviors. However, it does not explicitly contrast with sibling tools like file_issues, leaving some inference to the agent.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/rodlunt/engineering-audit'

If you have feedback or need assistance with the MCP directory API, please join our Discord server