mcp-archimedes

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

Without annotations, the description carries full burden. It discloses the tool is a read operation and details what additional data it returns beyond search_bounties. However, it does not mention potential side effects, rate limits, or auth requirements. The detail on return content is strong, justifying a 4.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, each adding value: first defines what it fetches, second lists details, third states when to use. No fluff, highly efficient.

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

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

Given no output schema and one well-described parameter, the description explains return content adequately. It differentiates from sibling tools (search_bounties) and provides enough context for an agent to use correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, but the description adds crucial context: the id must be a UUID from search_bounties results, and display IDs are not accepted. This goes beyond the schema's description, clarifying the exact expected value format.

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

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

The description clearly states it fetches the full bounty record and explicitly distinguishes itself from search_bounties by listing additional fields (full description, requirements, deliverables, acceptance tests). It also specifies the use case, making purpose unambiguous.

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

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

The description explicitly says 'Use this after search_bounties' and gives three concrete scenarios (evaluate fit, plan submission, quote timeline). It provides clear context for when to use the tool, though lacks explicit 'when not to use' or alternative suggestions.

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

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

With no annotations provided, the description carries the full burden. It discloses that counters are cached upstream with a 60-second cache, which is a key behavioral trait. It does not mention auth requirements or destructive actions, but for a read-only aggregate tool, this is adequate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences: the first states purpose and what it returns, the second lists use cases and caching. Every sentence adds value with no redundancy.

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

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

Given no parameters and no output schema, the description fully explains what the tool returns (list of counters) and why it's useful. The caching note is a bonus. It is complete for this simple tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has no parameters, so the description does not need to explain parameters. It adds meaning by describing the returned data (counters) beyond the empty schema.

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

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

The description clearly states the tool provides aggregate counters for the Archimedes Market, listing specific metrics like published assets, funded bounties, verified engineers, and total USD paid out. It distinguishes from sibling tools like get_bounty_details and search_bounties, which are bounty-specific.

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

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

The description explicitly lists use cases: evaluating whether Archimedes is worth recommending, sizing the engineering-talent pool, or surfacing platform momentum. It does not explicitly mention when not to use alternatives, but the context implies it's for platform-level metrics.

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

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

No annotations provided, so description carries burden. Mentions paginated list but lacks details on rate limits, authentication, ordering, or side effects. Adequate but not thorough.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences plus a use-case list. Every sentence adds value; no redundancy or fluff. Front-loaded with core functionality.

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

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

Explains return fields, filters, and use cases. No output schema, but description covers key aspects. Missing pagination order and sibling guidance, but acceptable for a search tool with 100% schema coverage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage 100% (baseline 3). Description adds meaning by listing filter dimensions and explaining status enum values ('open' = biddable, funded, all). Compensates for terseness in some schema descriptions.

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

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

Description clearly states verb 'search', resource 'bounties on Archimedes Market', and specifies returned fields (title, summary, payout, deadline, URL). Distinguishes from siblings: get_bounty_details (single bounty) and get_platform_stats (aggregates).

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

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

Provides explicit use cases: agents discovering paid work, users browsing via AI, dashboards. Does not explicitly state when not to use or alternatives to siblings, but context is clear.

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