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Glama

Deps Dev

by io.github.pipeworx-io

Recall

recall
Read-onlyIdempotent

Retrieve a value previously saved via remember, or list all saved keys (omit the key argument). Use to look up context the agent stored earlier — the user's target ticker, an address, prior research notes — without re-deriving it from scratch. Scoped to your identifier (anonymous IP, BYO key hash, or account ID). Pair with remember to save, forget to delete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyNoMemory key to retrieve (omit to list all keys)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "key": "user_research_topic"
+  },
+  {}
+]
  2. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already establish read-only, idempotent, and non-destructive behavior, so the description need not repeat them. It adds valuable context about scoping to the agent's identifier and the behavior of omitting the key argument to list all keys.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three tight sentences cover operation, use case, and companion tools, with no filler or repetition.

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?

The tool is simple (one optional parameter, no output schema), and the description covers purpose, usage, and scoping. However, it never explicitly describes the return value's shape, relying on inference from 'retrieve a value' and 'list all saved keys.'

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?

The schema fully documents the `key` parameter with 100% coverage, but the description enriches it with concrete examples (target ticker, address, research notes) and clarifies the omission behavior.

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 opens with a precise action: 'Retrieve a value previously saved via remember, or list all saved keys (omit the key argument).' This explicitly names the sibling tools `remember` and `forget`, distinguishing it from related memory operations.

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?

It states when to use the tool: 'Use to look up context the agent stored earlier... without re-deriving it from scratch.' It also provides alternatives: 'Pair with remember to save, forget to delete.'

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

A3.6/5.0
Disambiguation2/5

Multiple tools overlap heavily: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are nearly identical routers, the six polymarket tools cover similar prediction-market territory with fuzzy boundaries, and the deps.dev tools (package/version/dependencies/query/scan_dependency) all deliver dependency metadata. An agent would frequently need the lengthy descriptions to pick the right one.

Naming Consistency2/5

Tool names mix several conventions: noun-only names (package, version, query, project, dependencies), verb_noun names (scan_dependency, validate_claim, resolve_entity), and family-prefixed names (ask_pipeworx_*, polymarket_*, pipeworx_*). There is no single consistent pattern across the set.

Tool Count2/5

With 36 tools, the server is well past the 'heavy' threshold. The scope is also sprawling: general data querying, dependency lookup, memory management, subscriptions, prediction markets, claim verification, and AI-visibility scanning. Many tools could be consolidated or moved to separate servers.

Completeness3/5

The tool set is individually broad and covers many workflows, but the server's stated identity ('Deps Dev') does not match the dominant Pipeworx data surface, creating an unclear core purpose. Within the dependency sub-domain it is fairly complete, and the data-research workflows have decent coverage, but gaps like subscription updates and true deps.dev ecosystem coverage suggest the surface is improvised.

Resources