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boltwork-mcp

boltwork-mcp

by Squidboy30
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

review_code_url

Fetch and review code from a GitHub or GitLab blob URL (auto-converted to raw). Costs 2000 sats via Lightning.

Instructions

Review code fetched from a URL. Supports GitHub and GitLab blob URLs (auto-converted to raw). Costs 2000 sats via Lightning.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "url": "<url>"
    },
    "name": "review_code_url"
  }
}

Input Schema

NameRequiredDescriptionDefault
urlYesURL to the code file (GitHub/GitLab/raw)
languageNoLanguage hint (optional)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.22

TDQS

A4.2/5.0
Behavior3/5

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

With no annotations, description adds value by disclosing auto-conversion of URLs and cost. Does not detail rate limits or authentication, but basic behavioral information is present.

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?

Two sentences, no redundant information, front-loaded with core functionality. Every sentence contributes.

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?

Covers essential aspects: supported URLs, cost, optional language hint. Lacks description of return format, but title implies review output; relatively complete for a simple tool.

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 covers 100% of parameters; description adds meaning by explaining url parameter accepts GitHub/GitLab blob URLs (auto-converted to raw) and language is optional hint.

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?

Description clearly states 'Review code fetched from a URL' and specifies supported platforms (GitHub, GitLab), distinguishing it from sibling tools like 'review_code' (likely direct input) and 'explain_code'.

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?

Provides context on supported URL types and cost (2000 sats via Lightning), guiding when to use. Does not explicitly exclude scenarios, but clarity on supported platforms suffices.

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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