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Quant Swarm Audit — Execute Strategy Audit

audit.run
Read-onlyIdempotent

Executes a reproducible Quant Swarm Audit job bundle with approval-token checks, idempotency deduplication, and a hard credit cap so retries and preflight refusals never trigger duplicate billing.

Instructions

Executes the Quant Swarm Audit and records a reproducible job bundle. Enforces approval_token verification, idempotency_key deduplication, and max_credits spend cap; never charges on preflight refusals.

Input Schema

NameRequiredDescriptionDefault
modeNoExecution mode: 'local' (0 credits) or 'hosted' (20 credits).local
max_creditsNoHard spend cap in credits (0 for local runs; >=20 for hosted runs).
trades_pathNoOptional trades path.
trades_rowsNoOptional inline trades rows.
preflight_idNoPreflight ID returned by `audit.preflight`.
random_seedsNoDeterministic bootstrap seeds (must match the seeds used in `audit.quote`).
returns_pathNoOptional returns path.
returns_rowsNoOptional inline returns rows.
strategy_nameNoStrategy identifier.candidate_strategy
approval_tokenYesInput-bound approval_token returned by `audit.quote`.
benchmark_pathNoOptional benchmark path.
benchmark_rowsNoOptional inline benchmark rows.
idempotency_keyYesCaller-supplied idempotency key to prevent duplicate execution or billing on retries.
cost_assumptionsNoOptional inline cost assumptions dict.
features_manifestNoOptional inline feature manifest dict.
cost_assumptions_pathNoOptional cost assumptions JSON path.
features_manifest_pathNoOptional feature manifest JSON path.

Output Schema

NameRequiredDescriptionDefault
howNo
modeNo
toolNo
errorNo
accessNo
job_idNo
reasonNo
statusNo
metricsNo
eligibleNo
findingsNo
gbp_costNo
job_id_aNo
job_id_bNo
next_stepNo
strategy_aNo
strategy_bNo
html_reportNo
max_creditsNo
credits_costNo
generated_atNo
input_sha256No
metrics_diffNo
new_warningsNo
preflight_idNo
random_seedsNo
has_benchmarkNo
strategy_nameNo
written_filesNo
approval_tokenNo
execution_planNo
input_sha256_aNo
input_sha256_bNo
trades_summaryNo
artifact_hashesNo
coverage_matrixNo
credits_chargedNo
idempotency_keyNo
markdown_reportNo
package_versionNo
returns_summaryNo
assessment_afterNo
cost_assumptionsNo
headline_metricsNo
not_tested_countNo
required_creditsNo
assessment_beforeNo
idempotent_replayNo
request_access_atNo
resolved_findingsNo
validation_errorsNo
counts_by_categoryNo
overall_assessmentNo
finding_transitionsNo
remediation_verdictNo
has_features_manifestNo
not_investment_adviceNo
outbound_data_previewNo
reproducibility_bundleNo
estimated_runtime_secondsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.0.0

TDQS

B3.4/5.0
Behavior3/5

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

It adds real behavioral context beyond the annotations: approval-token verification, idempotency-key deduplication, a max_credits spend cap, and the guarantee of no charge on preflight refusals. However, this billing/runnable-job behavior sits in tension with readOnlyHint=true, and the description does not reconcile that or explain what the recorded job bundle persists or how long it is retained.

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?

Two tight sentences, with the action front-loaded and the three enforcement guarantees following. No filler, though the compression leaves out sequencing that would have earned a 5.

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

Completeness3/5

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

With 17 parameters, an output schema, and full annotation coverage, the definition is workable but incomplete: it does not describe the required ordering (quote → preflight → run), how local vs hosted mode interacts with max_credits at call time, or what happens when an approval_token is stale or already consumed.

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% (mode, max_credits, seeds, per-artifact path/rows pairs, and the quote-derived approval_token are all documented in the schema), so the schema carries parameter meaning. The description adds only the credit/refusal framing and no additional parameter semantics, making the baseline 3 correct.

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?

"Executes the Quant Swarm Audit and records a reproducible job bundle" gives a specific verb (executes) plus resource (the strategy audit) and names the artifact produced (job bundle). It is clear on its own, but it never distinguishes itself from sibling tools such as audit.preflight, audit.quote, or audit.compare, so an agent cannot route between them from this description alone.

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?

The required approval_token and idempotency_key imply a prerequisite flow (quote-then-run) but the description never states when to call this instead of audit.preflight or audit.quote, nor any exclusion conditions. Usage is inferable from the schema rather than stated in the prose.

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