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Repro Capsule MCP

Repro Capsule MCP

by efficjump
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

add_artifact

Add a project file to a bug reproduction capsule as redacted text or a binary hash-only record for evidence.

Instructions

Add one reviewed project file as redacted text or a binary hash-only record.

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": {
      "case_id": "<case_id>",
      "relative_path": "<relative_path>"
    },
    "name": "add_artifact"
  }
}

Input Schema

NameRequiredDescriptionDefault
noteNoOptional provenance or reason for including this artifact.
case_idYesIdentifier returned by start_case.
relative_pathYesProject-relative regular file path; symlinks and sensitive names are denied.
include_binary_contentNoRequest binary contents; server-level binary opt-in is also required.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

The description adds context beyond annotations: it clarifies that content is either redacted text or a binary hash-only record. Annotations already indicate non-destructive mutation. However, it does not disclose behaviors like overwrite policy, size limits, or whether concurrent adds are allowed.

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 a single concise sentence that front-loads the key purpose. It efficiently conveys the tool's function without unnecessary words, though it could be slightly more specific about the case context.

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

Completeness3/5

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

With a complete schema and output schema, the description covers the high-level function but lacks guidance on when not to use the tool or how it integrates with sibling tools. Prerequisites are implied by the parameter description for case_id.

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 each parameter has a clear description (e.g., 'relative_path' denies symlinks). The description adds no specific parameter details beyond the schema, so baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'add' and the resource 'artifact' (as a project file), specifying two modes: redacted text or binary hash-only. While it doesn't explicitly mention 'case', the required parameter case_id implies the context. It distinguishes from sibling tools like 'analyze_case' or 'execute_plan' by focusing on adding content.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites (e.g., a case must exist) or when to choose redacted text vs. binary mode, leaving the agent to infer from parameters.

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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