Skip to main content
Glama

audit_action

Runs the Final Action Realism Audit (Audit Pass B) for a subject by checking eight True/False action criteria and returns PASS or a detailed failure report.

Instructions

Run the Final Action Realism Audit (Audit Pass B — 8 questions) for a specific subject. Pass the subject name and True/False for each question. Returns PASS or detailed failure report.

Input Schema

NameRequiredDescriptionDefault
subject_nameYes
gravity_correctNo
force_stops_motionNo
timing_matches_massNo
ground_contact_cleanNo
center_of_mass_drivesNo
follow_through_existsNo
weight_location_clearNo
force_initiates_motionNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.5.0

TDQS

B3.1/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the outcome contract ('Returns PASS or detailed failure report'), which is genuinely useful, but says nothing about side effects, whether results are persisted, idempotency, or what happens when only a subset of the eight booleans is supplied (all default to false).

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?

Three short sentences, front-loaded with the action, then invocation, then return behavior. Nothing is padded, though the brevity is partly under-specification rather than discipline.

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

Completeness2/5

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

For a 9-parameter tool with zero annotation coverage and zero schema coverage, the description is too thin. Output schema exists, so return values needn't be spelled out, but the eight audit criteria and the default-false semantics remain unexplained, leaving an agent unable to answer the audit correctly.

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 description coverage is 0% across 9 parameters, and the description only says '8 questions' with True/False answers. It does not define what any of gravity_correct, force_stops_motion, center_of_mass_drives, etc. actually mean, so an agent must guess at criterion interpretation and at the consequence of leaving defaults at false.

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

Purpose4/5

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

States a specific verb and resource: 'Run the Final Action Realism Audit (Audit Pass B — 8 questions) for a specific subject.' The 'Pass B' framing and the subject-scoped scope make it distinguishable from audit_camera, though it never names that sibling explicitly.

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?

'Pass the subject name and True/False for each question' gives a minimal invocation instruction but says nothing about when this audit should be run, prerequisites (e.g., must audit_camera / validate_gate run first), or what to do on failure. Usage is implied by the tool name rather than stated.

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