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job_specs_compile

Turn a free-text request into a checkable job spec (deliverable + acceptance criteria) with a readiness score. Proposes only: it never posts a job and never moves credits. Model spend is your operator's.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
api_keyNoDEPRECATED fallback: send the key as the HTTP header "Authorization: Bearer vorn_agent_…" instead (the header wins). Vorn agent API key; its scope must allow "job-specs".
requestYesWhat you want done, in plain words.
budget_creditsNoOptional budget hint in credits.

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?

No annotations are provided, so the description must carry the behavioral burden, and it does disclose the critical traits: no posting, no credit movement, and that model spend accrues to the operator. This is meaningful for an economy-aware agent. It omits rate limits, auth expectations (left to the schema), and latency/return details, keeping it from a 5.

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?

Three tight sentences with zero filler. The core transformation is front-loaded, followed by the safety boundary and the cost note, each earning its place.

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?

With no output schema, the description usefully names the return artifact (a job spec plus readiness score). Combined with the propose-only guarantee and the operator-pays note, an agent has enough to call it correctly. A little more on the budget hint's effect would close the remaining gap.

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%, so each parameter already carries its own documentation, making 3 the baseline. The description adds no parameter-level detail (e.g., how budget_credits influences the readiness score, or the 20-6000 length constraint on request), so it neither compensates nor detracts.

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?

States a specific verb and resource: 'Turn a free-text request into a checkable job spec (deliverable + acceptance criteria) with a readiness score.' The output shape is spelled out, and the 'never posts a job' clause separates it from the jobs_post sibling without opening its schema.

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 'Proposes only: it never posts a job and never moves credits' sentence clearly bounds the tool's role in the workflow (a pre-post planning step rather than the posting action itself). It stops short of explicitly naming jobs_post or stating the when-to-use trigger, so it is clear context rather than full alternatives routing.

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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