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portfolio-drift-mcp

portfolio-drift-mcp

by odanree
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

audit_portfolio_drift

Audits portfolio projects against their GitHub repos to detect and report drift.

Instructions

Audit every project in the portfolio against its GitHub repo.

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": "audit_portfolio_drift"
  }
}

Input Schema

NameRequiredDescriptionDefault
adapterNowhich portfolio backend to read from. "beacon" (default) or "file". The "file" adapter additionally requires DRIFT_PROJECTS_FILE.beacon
limitNostop after N projects. Useful for fast smoke tests — the full audit on a 25-project portfolio takes ~2-3 minutes.
modelNoAnthropic model id. Defaults to the env DRIFT_MODEL setting (claude-sonnet-4-6 if unset).

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It does not disclose behavioral traits such as whether the audit is read-only (destructive hint), side effects, or authentication requirements. The only behavioral insight comes from the 'limit' parameter description mentioning time consumption (~2-3 minutes for 25 projects), which is insufficient.

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 quickly conveys the core purpose. It is front-loaded and efficient, with no wasted words. However, it could include additional context without becoming verbose.

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

Completeness2/5

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

Despite having an output schema and three optional parameters, the description is minimal. It does not explain the overall audit process, success/failure behavior, or how it handles errors. The presence of sibling tools increases the need for more context, which is absent.

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%, so all parameters have detailed descriptions (e.g., adapter options, limit for smoke tests, model override). The tool description itself ('Audit every project...') adds no extra parameter meaning beyond what the schema already provides. Baseline 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 clearly states that the tool audits every project in the portfolio against its GitHub repo, which is a specific verb+resource. It distinguishes from the sibling tools 'audit_single_project' (single project) and 'apply_drift_patches' (applies patches) by focusing on all projects.

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

Usage Guidelines3/5

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

The description implies usage for a portfolio-wide audit, but does not explicitly state when to use this tool versus its siblings (e.g., 'For a single project, use audit_single_project'). No when-not or alternative guidance is provided, making it adequate but not explicit.

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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