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Snapback

by io.github.ra1labsworkx-wq
OverviewDiscussionsAdmin

submit_feedback

Tell Snapback whether a verdict was correct (correct=true/false), with an optional free-text note (did the fix work? what was wrong?). ONE rating per verdict — call it AFTER you act on a verdict and see the outcome. Your correction updates the SHARED pattern library (fix patterns are shared anonymized so every agent benefits; your trace content is never shared) — a right verdict comes back faster next time, a wrong one gets down-weighted. To ask for a new pattern or report an unsolved problem, use request_pattern instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteNooptional free-text: what worked, what was wrong, or any detail that would help us improve this verdict
correctYestrue if the diagnosis was right, false if not
verdict_idYesthe verdict you're rating

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "description": "A JSON object (returned as text in result.content[0].text). Diagnosis tools return {matched, family, fix, confidence, source, action_class, auto_safe, gate}; other tools return their own JSON result.",
+  "type": "object"
+}
  2. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations only declare the safety profile (readOnly=false, idempotent=false, openWorld=true); the description adds the substantive consequences: it mutates a SHARED pattern library, ratings reweight future verdicts, and trace content is never shared while patterns are anonymized. That privacy and side-effect disclosure is exactly what annotations cannot convey.

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 core action and the when-to-call rule, and each sentence carries distinct information (semantics, timing, shared-library effect, alternative). It is dense with em-dashes and parentheticals, but nothing is wasted.

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?

An output schema exists, so return values need no explanation, and annotations plus the description together cover safety, side effects, and data-sharing policy. For a 3-param feedback tool, an agent has everything needed to call it 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 description coverage is 100% and already documents verdict_id, correct, and note. The description's parameter info ('correct=true/false', note = 'did the fix work? what was wrong?') largely restates the schema, adding only framing rather than new syntax or constraints. Baseline 3 applies.

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 object ('Tell Snapback whether a verdict was correct') plus the payload shape (correct flag + optional note). It explicitly distinguishes itself from request_pattern, which covers the adjacent 'new pattern / unsolved problem' case.

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 timing ('call it AFTER you act on a verdict and see the outcome'), a cardinality constraint ('ONE rating per verdict'), and names the alternative tool (request_pattern) with the condition that selects it. Nothing is left to inference.

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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