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Search GitHub bounty issues

search_github_bounties
Read-only

Search open GitHub and Algora bounty issues by keyword, language, and minimum USD amount, returning newest listings with heuristically parsed rewards that may be missing or wrong.

Instructions

Search open GitHub issues labelled "bounty" or Algora's "💎 Bounty", newest first. Amounts are parsed heuristically from the title, labels and body and may be missing or wrong.

Input Schema

NameRequiredDescriptionDefault
limitNoMax results (1-50, default 20)
keywordsNoFree-text keywords
languageNoRepository / project programming language, e.g. "TypeScript"
min_amount_usdNoOnly return bounties worth at least this many USD (items with unknown amounts are excluded)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint, so the safety profile is covered. The description adds genuinely useful behavioral context beyond that: results are newest-first and bounty amounts are heuristically parsed and may be missing or wrong — a data-quality caveat the agent cannot infer from structured fields.

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 tight sentences: the first gives scope and ordering, the second gives the caveat. Nothing is wasted and the most important scoping information is front-loaded.

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?

For a search tool with no output schema, the description never says what a result contains (title, repo, URL, parsed amount, labels) or how ordering/limit interact with pagination. The core scope and the amount-reliability caveat are present, but return-shape information is missing.

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 coverage is 100%, so parameters are already documented (including the min_amount_usd note that unknown-amount items are excluded). The description reinforces this by explaining why amounts can be unreliable, which directly affects how much to trust amount-based filtering.

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?

States a specific verb and resource (search open GitHub issues labelled 'bounty' or Algora's '💎 Bounty') and adds ordering (newest first), so the agent knows exactly what corpus is covered. It does not name the sibling tools (search_bounties, search_opire_rewards), so platform differentiation is left implicit rather than stated.

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 scope constraint (open issues, specific bounty labels) implies when the tool applies, but there is no explicit guidance on when to prefer it over search_bounties or search_opire_rewards. No exclusions or prerequisites are stated.

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