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job_result

Fetch a finished proving job's result {image_id, total_cycles, journal_b64, receipt_b64}. 404 until done; results kept 24h. Free.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYes

TDQS

A4.1/5.0
Behavior4/5

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

No annotations provided, so description carries full burden. It discloses 404 behavior until completion, 24-hour retention, and that it's free. This is useful behavioral context beyond basic read operation.

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?

Extremely concise: two clear sentences with no filler. Front-loaded with purpose and output structure. Every word adds value.

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?

Given a single parameter and no output schema, the description lists the output fields and provides key behavioral constraints (404, 24h retention, free). Lacks examples or error handling details, but adequate for a simple fetch tool.

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

Parameters2/5

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

Schema coverage is 0%, and the description adds no extra meaning for the single parameter (job_id). It does not explain format, example, or how to obtain the job_id.

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 uses a specific verb ('Fetch') and identifies the resource ('finished proving job's result') with explicit fields. It distinguishes itself from siblings like job_status and prove_submit.

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 implies when to use (after job is finished) via '404 until done' and notes results kept 24h. It does not explicitly state when not to use or compare to alternatives, but the context is clear.

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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TDQS

A3.7/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose, with detailed descriptions that prevent ambiguity. Even within related domains (e.g., covenant operations, proving steps), the functions are well-separated and described.

Naming Consistency4/5

Most tools follow a verb_noun or noun_noun pattern with underscores, but there are some single-verb names like 'catalog' and 'classify'. Within subdomains naming is consistent (e.g., kaspa_*, covenant_*, prove_*). Minor deviations prevent a perfect score.

Tool Count3/5

36 tools is on the high side for a typical MCP server, but the broad scope (blockchain, payments, ZK proving, text processing, search, registry) justifies the count. It borders on being too large for easy navigation but remains reasonable.

Completeness4/5

The server covers a wide range of functionalities with no critical gaps for its stated domain. Minor gaps exist (e.g., no direct Kaspa send transaction tool), but the covenant tools provide a workaround. Overall, the surface is fairly complete.

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