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deprecated_operations

UNDERSTANDING — every provider publishing at least one operation marked deprecated in its own OpenAPI, ranked by how many. The lifecycle view of the catalog: 8,297 deprecated operations across 681 providers, which nothing could see before, because a provider's own deprecated filter needs you to already suspect that provider. Drill in with get_provider_operations(deprecated=true).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo
limitNo
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.

TDQS

A3.8/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It conveys that this is a read-only, catalog-wide, ranked list, but it does not describe response fields, pagination behavior, or any ordering direction beyond 'ranked by how many.' The core behavior is clear but under-specified.

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 includes several useful elements but also extraneous motivation ('which nothing could see before') and a hard-coded statistic (8,297 operations / 681 providers) that will age and does not help invocation. The core definition is front-loaded, but the extra context could be trimmed.

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 gives a solid conceptual model and a drill-in pointer, but with no output schema and no annotations, the agent must infer the return format and how page/limit affect results. It is adequate for a simple categorized list but not fully complete for a low-coverage schema.

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

Parameters2/5

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

Schema description coverage is only 33% (only 'context' has a schema description). The tool description itself says nothing about page, limit, or context, so it adds no meaning beyond the schema. Page and limit must be inferred from their names, and context is only explained in the schema, not reinforced.

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 states a specific verb and resource: it lists every provider with at least one deprecated operation in its own OpenAPI, ranked by count. It also explicitly names the drill-down sibling get_provider_operations(deprecated=true), which distinguishes this catalog-wide view from per-provider tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear when-to-use context: to see deprecated operations across the catalog without already suspecting a provider, because a provider's own deprecated filter requires prior suspicion. It also points to the exact alternative for drilling in, get_provider_operations(deprecated=true).

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.

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