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List project dependencies

list_dependencies
Read-onlyIdempotent

List every dependency your project's agents call, ranked by call volume, and see which agents call each model, tool, database, queue, HTTP, or RPC.

Instructions

Requires the read scope or higher. Everything the project's agents call, across every agent, most calls first: each dependency with the same figures as get_agent_dependencies plus agents (which agents call it, and how often). Answers questions such as which agents call postgres or use a model. At most 50 rows; more counts the rest. untrusted_fields names the data fields LastPing did not write (job output, exporter data or user-supplied names).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNoOnly one kind of dependency: model, tool, http, database, queue, rpc or agent. Omitted: all.
rangeNoTime window: 24h, 7d (the default) or 30d. It covers every UTC day that overlaps it, so 24h spans two days.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.1.17
    • changedInput schema / properties / kind / description
      Previous value: -"Only one kind of dependency: model, tool, http, database, queue, rpc or agent. Omit for all."New value: +"Only one kind of dependency: model, tool, http, database, queue, rpc or agent. Omitted: all."
  2. Addedv0.1.6

TDQS

A4.4/5.0
Behavior5/5

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

Adds substantial context beyond the annotations: the required auth scope (read or higher), a hard row cap of 50 with a `more` overflow count, and the meaning of `untrusted_fields` (data fields LastPing did not write). Annotations cover the safety profile, and the description layers on the operational constraints that matter for calling it correctly.

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?

Dense but front-loaded: the ordering, scope, and auth requirement come first, followed by pagination and untrusted-field notes. Each sentence carries information, though the passage is longer than strictly necessary for a two-parameter read tool.

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?

With no output schema, the description carries the return-shape burden and does so: per-dependency figures, the nested agents breakdown with call counts, the 50-row cap, and untrusted field notice. Nothing an agent needs to interpret results is missing.

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 100% and both enums are already documented (kind omitted = all, range default 7d with the UTC-day overlap note). The description does not add format or semantics beyond the schema, so the baseline 3 applies.

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 (dependencies the project's agents call) and an explicit scope distinction from the sibling get_agent_dependencies ('same figures as get_agent_dependencies plus agents'). An agent can tell it apart from the per-agent variant without opening either 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?

Gives concrete usage contexts ('which agents call postgres or use a model') and implicitly routes per-agent needs to get_agent_dependencies by contrasting the two. It stops short of an explicit when-not-to-use-this statement, so it lands just below the top band.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.