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Pick a library

pick_library
Read-onlyIdempotent

Given a coding task, recommend 1-3 libraries from the should-i-use index with one-line reasoning and an honest warning about the top pick. Use before installing anything.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskYesWhat you are trying to do, e.g. "parse CSV files in node"
ecosystemNoOptional registry filter

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
answerYesThe clamped text answer (hard limit ~500 tokens)

Schema Changelog

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

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already provide readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so the safety profile is covered. The description adds behavioral details beyond this: it returns 1-3 libraries, includes one-line reasoning, and provides an 'honest warning about the top pick.' This is useful context about the tool's conduct and output style.

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?

The description is exactly two sentences: the first is dense with purpose and output details, the second is a clear usage directive. No redundant words or repetition of schema/annotation information. It is front-loaded and earns every word.

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?

For a tool with only 2 simple parameters, a rich annotation set, and an existing output schema, the description covers all necessary aspects: what it does, output format, and when to use it. There is no missing critical context like permissions, side effects, or return behavior (covered by schema).

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% (both 'task' and 'ecosystem' have descriptions), so the baseline is 3. The description does not add new parameter semantics beyond the schema, but it reinforces that 'task' is a coding task and that the output recommendations depend on it. It doesn't introduce confusion or omit details.

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 uses a specific verb ('recommend') and resource ('should-i-use index'), and clearly states the output (1-3 libraries with reasoning and warning). It distinguishes itself from siblings like should_i_use (which likely evaluates a specific library) and audit_dependencies (which audits existing dependencies).

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 phrase 'Use before installing anything' provides clear timing/context. It doesn't explicitly name alternatives or exclusions, but the context implies this tool is for pre-installation selection. Sibling names are present but not referenced; a more explicit comparison would push this to 5.

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

A4.2/5.0
Disambiguation5/5

Each tool targets a distinct phase: deciding on a library (should_i_use, pick_library, alternatives), learning usage (how_do_i, docs_link), and auditing existing dependencies (audit_dependencies). There is no meaningful overlap between any two tools, as they clearly differentiate by input (task vs. library) and output (recommendation vs. snippet vs. docs).

Naming Consistency3/5

The names are all snake_case but mix imperative verbs (audit_dependencies, pick_library), nouns (alternatives, docs_link), and question phrases (how_do_i, should_i_use). This makes the set readable but not predictably patterned; an agent cannot anticipate a consistent verb_noun structure.

Tool Count5/5

Six tools is well-scoped for a library advisory server, covering selection, verification, documentation, usage, and dependency auditing without redundancy. The count is within the ideal range and each tool serves a distinct purpose.

Completeness5/5

The tool set covers the full lifecycle: pick a library (pick_library), evaluate it (should_i_use), see alternatives (alternatives), get usage snippets (how_do_i), get official docs (docs_link), and audit a project's dependencies (audit_dependencies). There are no obvious dead ends for common library decision workflows.