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get_rating_history

UNDERSTANDING — A provider's REAL score time series: one point per scored build (composite + agent readiness on each date), plus a summary of the movement over the window — first/last, net change, direction, and the largest single-build jump with the date it happened. Not an implied previous point; these are the recorded snapshots.

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.

TDQS

A3.5/5.0
Behavior4/5

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

No annotations exist, so the description carries the full burden. It discloses important behavioral traits: one point per scored build, composite plus agent readiness, and a summary of movement. Crucially, it clarifies that these are recorded snapshots, not implied or interpolated points, which is a meaningful non-obvious behavior that helps set expectations.

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 two sentences and contains no filler; it front-loads the core idea of a 'real score time series' and then adds the summary fields. The long dash-heavy first sentence is somewhat dense, but every clause contributes information about what the tool returns.

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 and no annotations, the description covers the return payload in useful detail: per-build points, composite and agent readiness, and summary fields. The main gap is the undocumented slug parameter and the exact response shape, but the prose is sufficient for an agent to invoke the tool with a provider identifier and understand what it will receive.

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?

The schema describes only the context parameter; the required slug has no description, and schema coverage is only 50%. The tool description does not compensate: it never explains what slug is, how to format it, or how it maps to a provider. With such low coverage, the description needed to handle this and did not.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the resource and output: a provider's score time series with composite and agent readiness per scored build, plus a movement summary. It makes the tool's purpose unambiguous. However, it does not explicitly name or distinguish sibling alternatives like get_provider_rating or whats_changed, so it falls short of a 5.

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: an agent would use this when it needs a provider's recorded score history over time. But there is no explicit guidance about when to choose this over sibling tools such as get_provider_rating, find_ratings, or whats_changed, and no when-not-to-use conditions are provided.

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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