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Python
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shadow_review_status

Read-only

Inspect daemon health and production telemetry: view config, recent passes, and outcome mix to validate if the loop's spawned evaluations justify Opus time.

Instructions

Show shadow-review config, recent passes, and production telemetry.

Snapshot for sanity-checking that the daemon is alive and advancing its cursor, PLUS the production-validation rollup (issue #6): for the 24h and 7d windows it aggregates how often the daemon fired, the outcome mix (no_window / too_short / spawned / deferred / error), the MATERIALIZED-vs-SKIP hit rate of spawned evaluator children, durable skill writes attributable to shadow_review, and the total Claude-spawn time spent — so you can tell whether the loop earns its Opus minutes or just emits SKIPs.

snapshot_path: when set, also writes a markdown report to that path for human review (the side-channel snapshot).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
snapshot_pathNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.14.0
    • addedInput schema / properties / snapshot_path
      Added value: +{
+  "default": "",
+  "title": "Snapshot Path",
+  "type": "string"
+}
  2. First observedv0.13.2

TDQS

B3.4/5.0
Behavior1/5

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

The description directly contradicts the readOnlyHint annotation by stating that setting snapshot_path 'writes a markdown report' as a side effect. This is a serious inconsistency. Furthermore, it does not disclose any other potential side effects or required permissions.

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

Conciseness3/5

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

The description is verbose with extensive technical details (e.g., MATERALIZED-vs-SKIP hit rate, Claude-spawn time) that could be condensed for quicker comprehension. While front-loaded with the core purpose, the additional detail makes it longer than necessary.

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 the tool has an output schema, the description does not need to explain return values. It covers the key capabilities and the optional file write. However, the contradiction with annotations detracts from completeness, and some details about configuration fields might be missing, but overall adequate.

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

Parameters4/5

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

The schema provides only the parameter name and default value. The description adds meaningful context by explaining that when snapshot_path is set, the tool writes a human-readable markdown report, thereby clarifying its optional side effect beyond what the schema conveys.

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 clearly states the tool shows shadow-review config, recent passes, and production telemetry. It specifies the snapshot's contents and contrasts it with alternative tools by mentioning what the production-validation rollup includes (e.g., outcome mix, hit rates), making the purpose specific and distinct from siblings like shadow_review_run.

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 description implies usage for sanity-checking daemon health and assessing if the loop earns its execution time. However, it lacks explicit guidance on when not to use this tool or how it compares to alternatives like candidate_review_status or shadow_review_run, leaving the agent to infer usage context.

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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