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apis-io

by io.apis

generate_artifact

INFLUENCE — REQUEST an artifact you are being marked down for not having: apis-json, agent-card, mcp (one tool per operation you already publish), arazzo, rules (a Spectral ruleset scoped to your own failing checks), scopes and security (read out of your own OpenAPI). Returns 202 — a person generates it against your live surface, checks it, and sends it to you. Nothing is published on your behalf either way: your score moves when YOU commit the file. Omit artifact to list what can be made.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYes
contextNoOptional: why you are asking. One sentence — the task you are trying to complete, or what you expect to get back. Never included in the answer and never used to rank; it is read only when a result turns out to be wrong, which is when knowing the intent is what makes the report actionable.
artifactNo

TDQS

A4.2/5.0
Behavior5/5

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

With no annotations, the description fully carries the burden. It discloses the 202 async response, the human-in-the-loop generation and checking, the fact that nothing is published automatically, and that the score changes only when the user commits the file. This is unusually transparent about side effects and process.

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?

The description is dense but efficient, front-loading the action and artifact list, with parenthetical clarifications that earn their place. The stylistic 'INFLUENCE' prefix adds a little noise, but overall the structure is compact and scannable.

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?

The description covers the async workflow, return code, list mode, and artifact semantics, which is strong given there is no output schema or annotations. However, it leaves the required 'slug' parameter unexplained and does not detail what the eventual delivery looks like, so completeness is partial.

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 only 33%, and the description compensates meaningfully for the artifact parameter by defining each enum value and the omission behavior. However, the required parameter 'slug' has no schema description and is not explained in the description, leaving a significant gap for the most important input.

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 action with a specific verb and resource: 'REQUEST an artifact' one is being marked down for not having, and enumerates the artifact types. It also differentiates the list mode ('Omit artifact to list what can be made'), making the tool's purpose unmistakable even among many find/submit siblings.

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 when to use it: when you are being marked down for a missing artifact. It also explains the list-mode behavior. It does not explicitly name alternatives or state when not to use it, so it stops short of a 5.

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

B3.1/5.0
Disambiguation3/5

Most tools are clearly separated by artifact type or resource (find_mcp vs find_openapi vs get_provider vs get_api), but the sheer volume creates some genuinely confusable clusters: apis_io_search vs find_apis vs find_artifacts, and insights_adoption vs insights_dimensions vs find_company_insights. Several readiness-related tools (what_can_i_fix, simulate_fixes, readiness_gates) also share a conceptual boundary, though their descriptions do help.

Naming Consistency3/5

The dominant patterns (find_*, get_*, cohort_*, compare_*) are consistent and predictable, but the set mixes in irregular names like apis_io_search, tag_group_tags, what_can_i_fix, whats_changed, and resolve. These deviations are readable but break the otherwise regular verb_noun convention.

Tool Count2/5

106 tools is far beyond the typical well-scoped server and will impose a heavy selection burden on agents. The server covers a genuinely broad domain (catalog search, ratings, cohorts, agent readiness, lists, exports, feedback), so the count is defensible in scope, but it is still too many to navigate efficiently.

Completeness5/5

The surface is remarkably complete: search and browse, single-entity detail, comparisons, cohort analytics, agent-readiness assessment, saved searches, list management, feedback/correction flows, and full dataset exports are all covered. There are no obvious dead ends, and even minor operations like re-running saved searches or simulating fixes are present.

Resources