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List bounty programs

list_programs
Read-only

Browse live, escrow-funded bug bounty programs. Optionally filter by a free text query over the name and summary. Returns each program's slug, top reward, currency, target count, response SLA, and a link.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax programs to return (default 25).
queryNoFree text filter over program name and summary.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the description does not need to restate safety. It adds valuable behavioral context by specifying that only 'live, escrow-funded' programs are returned and enumerating the fields returned per program. This goes beyond what annotations provide and helps the agent understand the tool's exact scope and output, though it does not mention potential nuances like pagination or rate limits.

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 two sentences with no filler. The primary purpose is front-loaded in the first sentence, and the second sentence efficiently covers filtering and return contents. Every phrase earns its place, making it easy for an agent to parse quickly.

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 read-only listing tool with two optional parameters and no output schema, the description is largely complete. It states the scope, filtering capability, and return fields, which is sufficient for an agent to call it correctly. It could mention the default limit or pagination, but the schema already covers those details, so the description is adequately complete for the tool's complexity.

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%, and the input schema already fully documents both limit and query, including their meaning and defaults. The description's 'free text query over the name and summary' paraphrases the schema without adding new semantic information. Since the schema does the heavy lifting, 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 opens with a specific verb and resource, 'Browse live, escrow-funded bug bounty programs', which clearly identifies this as a read-only listing operation. The mention of 'live, escrow-funded' narrows scope and distinguishes it from sibling tools like get_program, which targets a single program. An agent can immediately know what this tool does and how it differs from related list tools.

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?

The description explicitly states the tool browses programs and supports an optional free-text filter, providing clear context for when to use it. It does not explicitly mention alternatives or exclusions, such as 'use get_program for a single program', but the purpose is obvious enough that an agent can infer the appropriate use case. Overall, it gives clear functional context without explicit when-not guidance.

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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