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mcp-knowledge

by io.github.getgapup

oss_dependency_velocity_tracker

Read-onlyIdempotent

As a CTO, track the update velocity of your project's open-source dependencies to assess their impact on DORA metrics like deployment frequency and lead time. This tool fetches release history and version adoption data from npm registry and libraries.io, providing insights into dependency freshness, update frequency, and potential risks. Input a list of package names and optional version ranges to analyze. Outputs structured dependency velocity metrics and warnings about stale or rapidly changing packages.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asyncNoIf true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client timeouts.
packagesYes
lookbackDaysNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusYes
metricsNo
sourcesNo
warningsNo

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint. The description adds that the tool 'fetches release history and version adoption data from npm registry and libraries.io', confirming external data fetching and non-destructive behavior. It doesn't mention rate limits or async behavior, but the schema covers the async parameter.

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 a concise 3-sentence paragraph. It front-loads the purpose and quickly defines inputs and outputs. The first sentence targeting 'As a CTO' adds slight verbosity but is acceptable. Overall, it is tidy and to the point.

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 core intent, input, and high-level output (metrics and warnings). Since an output schema exists, detailed return values aren't needed. However, it omits mention of the async parameter for long running tasks and doesn't explain the lookbackDays parameter, which reduces completeness for a 3-parameter tool.

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 description coverage is only 33% (only async described). The description explains that packages expects 'a list of package names and optional version ranges', adding meaning beyond the schema for that parameter. However, it fails to mention the lookbackDays parameter or the structure of version ranges, leaving a gap for 2 of 3 parameters.

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 explicitly states it tracks 'update velocity' of open-source dependencies and links to DORA metrics, which is a specific verb+resource. It distinguishes from siblings like dependency_vulnerability_scan (vulnerabilities) and social_engagement_velocity_tracker (social media) by focusing on dependency freshness and velocity.

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 clearly implies the use case: assessing dependency impact on DORA metrics. It doesn't explicitly state when not to use or provide alternatives, but the context of sibling tools makes differentiation clear. A dedicated exclusions list would improve it.

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

C2.8/5.0
Disambiguation2/5

Many tools have overlapping purposes, especially in competitive intelligence, ESG, and risk assessment. For example, there are multiple tools for competitor analysis (competitive_deep_dive, competitor_intel, competitor_moves, etc.) with unclear boundaries. Agents would struggle to select the correct tool without deep understanding of subtle differences.

Naming Consistency2/5

Tool names are a mix of English and French, and follow no consistent pattern. Some use snake_case (e.g., abm_architect, action_plan_esg), while others are verb-focused (e.g., content_catalog, fx_rate). The lack of a uniform naming convention makes it hard for agents to predict tool names.

Tool Count1/5

With 271 tools, the server is excessively large. Even for a broad knowledge domain, this number of tools makes discovery and selection inefficient. Typical coherent servers have 3-15 tools; this has an order of magnitude more, indicating poor scoping.

Completeness3/5

The tool set covers many domains (compliance, finance, marketing, HR, etc.), but the coverage is uneven due to redundancy. Key areas have multiple overlapping tools, while some sub-domains may still have gaps. Overall, the surface is broad but not well-curated.

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