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inspect_requests

Read the project's request inspector: the most recent requests that hit the mock API (method, path, query, status, origin, captured headers incl. x-* — authorization redacted to its scheme — and a body snippet for writes). Use it to VERIFY what your app / tests / webhook sender actually sent: point code at the mock, run it, then inspect. Pairs with custom_route catch-all bins (e.g. /webhooks/*) for webhook payload + signature debugging. Requires the adminKey, except project "demo" whose inspector is public.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNewest N entries to return (default 20, max 50).
projectYesProject id.
adminKeyNoProject adminKey (not needed for demo).

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations provided, the description carries the full behavioral burden and largely meets it: it discloses the adminKey auth requirement with the 'demo' exception, flags that authorization is redacted to its scheme only (a data-hygiene guarantee), and implies read-only behavior via the 'Read' verb and scope (most recent requests, newest N). Minor omissions like empty-state behavior and rate limits are acceptable for an inspection tool.

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?

Front-loaded with the core purpose, then a dense field list, then usage workflow, pairing note, and auth caveat in descending importance. Every clause earns its place — the captured-field enumeration, the VERIFY workflow, and the adminKey requirement are all load-bearing. Slightly long, but not padded; a tight 4.

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 there is no output schema, the description compensates by spelling out exactly what the inspector returns (method, path, query, status, origin, headers, body snippet) — so an agent knows the return shape. Combined with the auth caveat and usage workflow, everything required to call this tool correctly is present. Could be a 5, but the demo-project special case and auth mechanics are stated somewhat tersely.

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 coverage is 100%, so the baseline applies — the schema already documents limit, project, and adminKey. The description adds only marginal value: it clarifies that adminKey is 'not needed for demo' (reinforcing the schema note) and ties 'Newest N entries' to the limit field. This is helpful but does not substantially exceed what the structured schema already 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?

States a precise verb-resource pair ('Read the project's request inspector') and enumerates the exact captured fields (method, path, query, status, origin, headers incl. x-*, body snippet). This clearly differentiates it from the sibling mutation/CRUD tools (write_record, delete_project, import_data) — it is the observation counterpart, which an agent can grasp without opening any other 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?

Provides an explicit, actionable workflow: 'point code at the mock, run it, then inspect' to VERIFY what was actually sent. It also names its natural companion (custom_route catch-all bins for webhook debugging). It falls just short of a 5 because it never explicitly states when not to use it or names an exclusionary alternative.

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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TDQS

A4.4/5.0
Disambiguation5/5

Each tool maps to a distinct resource/operation: project lifecycle, resource seeding, artifact import, record CRUD, custom routes, snapshots, request inspection, and external API status. Even the data-population tools are clearly separated by existing project (add_resource) versus new project (import_data/create_project).

Naming Consistency4/5

Most tools follow a clear verb_noun pattern (add_resource, create_project, query_records, write_record, delete_project, etc.). A few noun-style names (custom_route, project_info, snapshots) break the pattern, but all names are snake_case and readable.

Tool Count5/5

Eleven tools is a well-scoped set for a mock API server: project creation/deletion, data population/import, record operations, snapshots, custom routes, inspection, and API status all have dedicated tools without redundancy.

Completeness4/5

The core workflow is well covered: create/delete projects, add/import resources, CRUD records, snapshot state, define routes, and inspect requests. The main gaps are the lack of explicit resource deletion and custom-route update/delete, but these are workaroundable rather than blocking.

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