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Find Good First Issues

find_good_first_issues

Finds beginner-friendly open issues, scores each for scope clarity, and flags mislabeled ones that touch core architecture despite the 'good first issue' label.

Instructions

Finds open issues labeled for beginners/first-time contributors, then scores each for genuine clarity of scope and flags ones that look mislabeled (e.g. touches core architecture despite the 'good first issue' label).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repoYesRepository name, e.g. 'anthropic-sdk-python'
ownerYesRepository owner or organization, e.g. 'anthropics'

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the disclosure burden and goes beyond the basic lookup by revealing notable behavior: each issue is scored for genuine scope clarity and mislabeled issues are flagged, with a concrete example. It does not detail output format or scoring criteria, but the key non-obvious behaviors are communicated.

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?

The description is a single sentence that front-loads the core action and then adds the scoring/flagging behavior. There is no filler, and every clause contributes meaningful information beyond the schema.

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 simple tool with two required parameters and no output schema, the description adequately conveys what the tool does and what the agent can expect conceptually: scored issues and mislabel flags. Exact output formatting is omitted, but that is minor given the straightforward input contract.

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?

The description adds no parameter-specific detail, but schema coverage is 100% and both owner and repo are already documented in the input schema. The description doesn't need to compensate, so the baseline of 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?

The description specifies a distinct action: finding open issues labeled for beginners/first-time contributors, then scoring scope clarity and flagging mislabeled ones. This clearly distinguishes it from sibling tools like get_repo_health, summarize_recent_commits, and ask_repo.

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 intended use is implied: use this when you want beginner-friendly issues from a repo. However, the description provides no explicit when-to-use/when-not-to-use guidance and names no alternatives or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.