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Codeforces

by io.github.pipeworx-io

Scan Dependency

scan_dependency
Read-onlyIdempotent

Composite "should I add this npm package to my project" check in ONE call — fans out across deps.dev (license + advisories + version history) and bundlephobia (gzipped/minified bundle size, dependency count, ESM/tree-shake support). Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me". Returns a summary block (is_latest, license, published_at, advisory_count, bundle_kb_min, bundle_kb_gz, dependency_count, has_esm, tree_shakeable), per-advisory detail, links, and a list of recent alternative versions. NPM ecosystem only in v1; PyPI / Maven / Cargo / Go fall under deps.dev:version directly. Partial failures degrade gracefully — bundlephobia's first measurement on a new version can take 5-30s; sources_failed will list it if it times out, the rest still returns.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
packageYesnpm package name. Scoped packages (e.g. "@types/node") are accepted.
versionNoSpecific version to check (e.g., "18.3.1"). Defaults to the latest published version when omitted.

TDQS

A4.6/5.0
Behavior5/5

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

Beyond annotations (readOnlyHint, openWorldHint, etc.), the description discloses critical behavioral details: composite nature, partial failure handling, and a 5-30s delay for bundlephobia first measurement with sources_failed reporting. This adds significant transparency.

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 front-loaded with purpose and structure, but slightly verbose. Every sentence adds value, though some details (e.g., bundlephobia timing) could be more succinct. Still, well-organized and informative.

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?

Given the tool's complexity (composite, multiple sources, partial failures, no output schema), the description covers all essential aspects: return fields, failure mode, ecosystem scope, and version handling. Complete for an AI agent's decision-making.

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 coverage is 100%, and the description adds minimal extra meaning: scoped packages accepted, version defaults to latest. Baseline 3 is appropriate as the schema already documents parameters thoroughly.

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 clearly defines the tool as a composite check for npm packages, combining deps.dev and bundlephobia. It specifies the exact use case: evaluating whether to add a package based on safety, popularity, and size. This distinguishes it from sibling tools like deps.dev:version for other ecosystems.

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?

Explicit usage guidance is provided: use when asked about package safety, popularity, or cost (e.g., 'is X safe / popular / small'). It specifies NPM-only scope and directs other ecosystems to deps.dev:version, offering clear when-to-use and alternatives.

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

B3.2/5.0
Disambiguation2/5

The set mixes Codeforces-specific tools with a large Pipeworx data toolkit. Within the Pipeworx family, ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are nearly identical (the beta explicitly matches the stable version today), and deep_research/discover_tools/suggest_questions also overlap as meta entry points, creating real selection hazard. An agent could easily misselect among these.

Naming Consistency2/5

Naming patterns are mixed: some tools use verb_noun (list_subscriptions, validate_claim, resolve_entity), some use bare verbs (remember, forget, recall), and some are noun phrases (problemset, blog_entry_view, recent_actions). Word order also varies (contest_list vs list_subscriptions), so no consistent convention is followed.

Tool Count2/5

39 tools is far too many for a server named 'Codeforces' — only 8 tools actually concern Codeforces, while the remaining 31 are unrelated Pipeworx/utility tools. This bloats the surface and makes the server feel unfocused, especially for an agent expecting a compact Codeforces API.

Completeness3/5

For the Codeforces domain, the core read-only API is covered (contests, standings, problems, user info/rating/status, blog entries, recent actions) but some endpoints are missing (blog comments, rated list, problem statements). The large number of extra tools does not fill these gaps and instead obscures the intended purpose.

Resources