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NextConstraint

by app.nextconstraint
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Fix prompt

get_fix_prompt
Read-onlyIdempotent

A ready-to-use fix prompt, written by NextConstraint, for the current constraint (omit issue_id) or for one alert, in the format for the chosen coding tool. It carries the evidence, the task, safety rules (new branch, show the diff, never touch billing, auth, user data or secrets) and how to check the fix worked. After shipping, call mark_fix_done with the commit SHA (see the fix-workflow prompt) rather than just marking it done.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_fix_prompt"
  }
}

Input Schema

NameRequiredDescriptionDefault
toolNoWhich coding tool the prompt is for.claude_code
issue_idNoAn alert id from list_alerts. Omit for the current constraint.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Beyond the annotations, it discloses the prompt's contents, including evidence, task, safety rules, and verification steps, and it explains the post-fix workflow with mark_fix_done. It does not describe return format or any generation constraints, but with readOnlyHint and idempotentHint already present, the added behavioral detail is substantial.

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 front-loaded with the core purpose and uses three economical sentences, with the safety rules and follow-up workflow placed afterward. The parenthetical safety list is dense but useful, and no sentence is clearly wasted.

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 prompt-generation tool with no output schema, the description explains what the returned prompt contains and what to do after shipping. It does not state the exact return shape, but the surrounding workflow and annotations make the definition sufficiently complete.

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 100%, and the description largely restates what the schema already says: omit issue_id for the current constraint and choose a coding tool format. It adds minimal parameter meaning beyond the existing schema descriptions, so the baseline of 3 is appropriate.

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 description states a specific resource and behavior: it returns a ready-to-use fix prompt for the current constraint or a single alert, formatted for a chosen coding tool. It also implicitly distinguishes the two modes via issue_id, so an agent can tell how this differs from get_current_constraint and get_alert.

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?

It clearly says to omit issue_id for the current constraint and to provide an alert id for one alert, and it gives the follow-up workflow after shipping by naming mark_fix_done. It does not explicitly compare against sibling tools like get_current_constraint or list_alerts, so it stops short of full when-versus-when-not guidance.

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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