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jeneric
by jeneric

resolve_system

Turn a free-text system description into candidate DISA STIG benchmarks, showing which apply to the named product build and noting missing versions.

Instructions

Resolve a free-text system description to candidate DISA STIG(s). Returns 'candidates' and 'notes'. limit caps the number of distinct benchmarks returned, not rows: a benchmark holding more than one STIG major (for example vSphere 8.0) contributes every major as its own row, so a caller asking for limit=5 may receive more than 5 rows. Include the product build where one exists (e.g. 'ESXi 8.0 U3'); each candidate reports whether it applies to that build in the 'applicable' field. When the description names a product version this knowledge base does not hold, a note in 'notes' says so and names the versions it does hold. A description naming more than one system is split on 'and' and commas and each part judged separately, so it can carry one such note per part, each quoting the part it is about. When more benchmarks tie with the last benchmark shown than limit allows, a note in 'notes' says how many and suggests calling again with a higher limit. If the knowledge base is not built yet this returns {"status": "not_ready"} with the commands to run, rather than an error.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
system_descriptionYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A4.5/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and discharges it: it explains the limit semantics (caps distinct benchmarks, not rows, and can yield more rows than limit), the 'applicable' field, the tie-overflow note, and the not_ready status with remediation commands instead of an error. This is unusually rich operational disclosure.

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

Conciseness4/5

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

Purpose and return shape are front-loaded, and each sentence carries information. It is dense and runs long, with the tie-note and multi-part-note behavior occupying separate sentences that could be tightened, but nothing is filler.

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

Completeness5/5

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

No output schema exists, so the description must describe returns itself; it names 'candidates', 'notes', the 'applicable' field, and the not_ready shape. For a 2-parameter lookup tool with no annotations, everything an agent needs to call and interpret it is present.

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

Parameters5/5

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

Schema coverage is 0%, so the description must compensate and does: limit is explained in depth (benchmarks vs rows, multi-major benchmarks contributing several rows), and system_description gets guidance on including build strings and how multi-system input is parsed. Both parameters gain meaning beyond their bare schema titles.

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 opening sentence states a specific verb (resolve) and resource (free-text system description → candidate DISA STIGs), and the tool is clearly distinguishable from siblings like list_stigs or search_techniques. An agent can tell what it returns ('candidates' and 'notes') without opening any schema.

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?

It gives strong input-shaping advice (include the product build, multi-system descriptions are split on 'and'/commas) but never states when to prefer this over list_stigs or another sibling, nor any explicit when-not-to-use condition. Usage is implied rather than contrasted against alternatives.

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