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Codeforces

by io.github.pipeworx-io

Generate llms.txt

generate_llms_txt
Read-onlyIdempotent

Generate a production-ready llms.txt file for any URL so AI crawlers (ChatGPT, Claude, Perplexity) can index the site cleanly. Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format. Output is a single text blob ready to drop at site-root/llms.txt. Useful for: getting a client's site indexed by AI, drafting llms.txt for your own project, or auditing how an AI crawler would see a competitor.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesFull URL of the site to summarize, e.g. "https://example.com" or a specific landing page.
max_linksNoMaximum number of link entries to include (default 25, max 50).

TDQS

A4.3/5.0
Behavior4/5

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

Description discloses that it fetches pages, extracts data, and emits standard markdown. Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds value by naming the output format and use context, but could mention error handling or rate limits.

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 sentences with no redundancy. Front-loaded with the main purpose, followed by how it works and usage examples. Every sentence is essential and well-placed.

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 simple tool with two parameters and no output schema, the description covers purpose, workflow, output format, and usage scenarios. Annotations handle safety concerns. No gaps remain.

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 has 100% coverage with clear descriptions for both parameters (url and max_links). The description mentions default 25 and max 50 for max_links, which is already in the schema, so minimal additional meaning beyond what the schema provides.

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?

Description clearly states the tool generates a production-ready llms.txt file for any URL, specifying the verb 'generate' and the resource. It distinguishes from siblings like ai_visibility_check by focusing specifically on llms.txt generation, and provides concrete use cases.

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?

Explicitly lists three usage scenarios: getting a client's site indexed, drafting for own project, or auditing competitor. Does not explicitly mention when not to use or alternatives, but the context is sufficient to infer appropriate use.

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