Mockbird

query_records

GET records from a mock resource. params is an object of query parameters, all optional: exact filters (field=value), operator suffixes (price_gte, date_lte, name_like, status_ne), full-text q, _sort/_order (or _page/_limit for pagination), select (field projection, e.g. "name,price"), _expand=/_embed= relations. Failure simulation for testing: mock_status=503 forces that status, mock_delay=2000 adds latency (ms), mock_chaos=0.3 fails that fraction of requests randomly, mock_seq=503,503,200 serves a deterministic status sequence (fail twice then succeed — best for retry tests), mock_jitter=500 adds random latency, mock_envelope=data wraps the response. Pass id to fetch a single record. Defaults to _limit=25 — pass _limit explicitly for more (max 100 per page).

Input Schema

TableJSON Schema

Name	Required	Description
`id`	No	Single record id. Optional.
`params`	No	Query params as key→value. Optional.
`project`	Yes
`resource`	Yes	Resource name (e.g. products).

TDQS

A4.8/5.0

Behavior5/5

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

With no annotations provided, the description carries the full burden and excels. It discloses failure simulation (mock_status, mock_delay, mock_chaos, mock_seq, mock_jitter), envelope wrapping (mock_envelope), and default limit behavior—all beyond the schema.

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

Conciseness5/5

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

The description is dense yet well-organized into a single paragraph. It front-loads the purpose and then systematically covers parameter details, failure simulation, and defaults—every sentence earns its place without redundancy.

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?

The description covers all query capabilities, failure modes, pagination, and projections. With no output schema, it doesn't detail the exact return shape, but the mock context and envelope mention provide adequate context for an agent to understand what to expect.

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?

The schema only describes params as 'Query params as key→value,' but the description details exact filter suffixes, full-text search, sorting, pagination, field projection, relation expansion, and all mock controls. This adds immense meaning beyond the schema.

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 opens with 'GET records from a mock resource,' clearly stating the verb, resource, and mock nature. This distinguishes it from sibling write tools like write_record and create_project, making the purpose unambiguous.

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?

The description gives clear context for querying (e.g., 'Pass id to fetch a single record') and mentions pagination defaults. However, it does not explicitly name alternatives or exclusion criteria, relying on the GET verb and sibling names to imply read-only usage.

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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