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dependency_risk

When to call: before you connect to or recommend an MCP server, when you care whether its declared dependencies were observed dead or dormant in the lastseen.dev register. Returns: dated facts, not a score: depends_on[], dead_dependency_count, dormant_dependency_count, n, provenance. Empty depends_on or zero counts means no dependency edges were on record for that id as of the response, not a guarantee of zero risk. Example: {"id":"io.github.06ketan/medium-ops"} id: MCP schema-server identifier whose dependency edges to inspect (e.g. io.github.owner/name).

Input Schema

NameRequiredDescriptionDefault
idYese.g. io.github.owner/name

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden and does so well: it specifies the return shape (depends_on[], counts, n, provenance), warns that the answer is factual rather than a risk score, and cautions that empty/zero results mean 'no edges on record,' not absence of risk. It omits any auth or rate-limit notes, but for a read-only register lookup that is minor.

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?

Front-loads the trigger with a 'When to call' label, then returns, then an example — an efficient, scannable structure. Slightly redundant in restating the id parameter at the end, but every sentence contributes.

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?

No output schema exists, so the description correctly documents the return fields and their interpretation limits, which is exactly what an agent needs. Combined with the trigger and example, nothing essential for correct invocation is missing.

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

Parameters4/5

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

Schema coverage is already 100%, so the baseline is 3, but the description adds genuine meaning: it defines the id as an 'MCP schema-server identifier whose dependency edges to inspect' and supplies an example value. It clarifies what is being looked up rather than merely restating the field name.

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?

States a specific verb+resource ('dependency edges to inspect' for a given MCP schema-server id) and explicitly distinguishes the output from a sibling by saying it returns 'dated facts, not a score,' which sets it apart from trust_score. An agent can identify the tool's function without opening the schema.

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?

Provides an explicit 'When to call' clause tied to a concrete moment (before connecting to or recommending an MCP server) and a condition (you care whether dependencies were dead or dormant). It stops short of naming an alternative tool or stating when-not-to-use, so it is clear context without full routing guidance.

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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