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Validate Claim

validate_claim
Read-onlyIdempotent

"Is it true that…" / "fact check" / "verify the claim that…" / "did X really…" / "was Y actually…" / "confirm or refute" / "true or false" — natural-language claim verification against authoritative sources. Use whenever the agent needs to check whether something a user said is factually correct. Company-financial claims (revenue, net income, cash for public US companies) verify via the structured SEC EDGAR + XBRL fast path with exact percent-delta math; ANY OTHER factual claim (macro statistics, rates, prices, drug data, records) automatically falls through to the grounded pipeline — routed to the right live source, answered with verbatim evidence, then judged. Returns a verdict (confirmed / approximately_correct / refuted / inconclusive / unsupported / could_not_verify), the grounded or structured actual value with pipeworx:// citation, and reasoning. IMPORTANT for callers: could_not_verify means the check did not happen (our LLM or source failed) and carries verification_error{stage,detail} — it is NOT evidence for or against the claim, and must not be shown as one. unsupported means we looked and cover no source for it. Replaces 4–6 sequential calls (NL parsing → entity resolution → data lookup → comparison).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
claimYesNatural-language factual claim, e.g., "Apple's FY2024 revenue was $400 billion" or "Microsoft made about $100B in profit last year".
tolerance_pctNoMax percent deviation still graded approximately_correct (0.5–50). Overrides the tolerance implied by the claim wording — set 1–2 for hallucination detection where any material error must be refuted. Default: implied by wording, capped at 5.

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive hints, and the description goes beyond them by detailing the semantics of 'could_not_verify' (check did not happen, not evidence) and 'unsupported' (no source found). This additional context is critical for correct interpretation of results.

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 dense but every sentence earns its place: trigger phrases, architectural distinction, verdict list, evidence format, and caller warnings. It is somewhat long but well-structured and free of redundancy.

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 fully explains the return values (verdict enum, grounded/structured value with citation, reasoning) and error handling. It covers both claim categories and provides an important warning about 'could_not_verify', making it complete for a tool of this complexity.

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?

Schema coverage is 100%, so the baseline is 3. The description adds significant value by explaining that tolerance_pct overrides the tolerance implied by the claim wording, has a default capped at 5, and is recommended at 1–2 for hallucination detection—details not present in the schema.

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 states the tool performs natural-language claim verification against authoritative sources, with explicit trigger phrases and a distinction from generic Q&A. It also notes that it replaces a multi-step pipeline, making its purpose unambiguous and differentiating it from sibling tools like ask_pipeworx.

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 description explicitly says 'Use whenever the agent needs to check whether something a user said is factually correct' and provides trigger phrases. It also explains the dual-path behavior for financial vs. other claims. It does not name alternative sibling tools, but the usage context is clearly specified.

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

A3.5/5.0
Disambiguation2/5

The 4 Codewars tools (kata, user, user_authored, user_completed) are distinct, but the 31 Pipeworx tools create real overlap: ask_pipeworx, ask_pipeworx_beta (explicitly 'currently matches ask_pipeworx exactly'), and ask_pipeworx_grounded are near-twins of the same router, and the five polymarket_* tools (edges, arbitrage, edge_tracker, fill_risk, kalshi_spread) have heavily overlapping opportunity-discovery purposes. discover_tools and suggest_questions also both serve as 'what can I ask' entry points. Agents will misselect between the three ask_pipeworx variants and across the prediction-market suite.

Naming Consistency2/5

Naming conventions are mixed: bare nouns (kata, user), bare verbs (forget, remember, subscribe), adjective_noun (recent_alerts, recent_changes), verb_noun (validate_claim, bet_research), and noun_verb (user_authored, user_completed) all appear. Even within the small Codewars family the prefix style is inconsistent — kata and user are bare nouns while user_authored and user_completed expect a user_ prefix, and remember/recall/forget use a different verb style than the rest of the server.

Tool Count2/5

35 tools exceeds the 25+ 'too many' threshold for a coherent server. Worse, 31 of the 35 are Pipeworx meta-research tools unrelated to the server's namesake (Codewars), so the count is drastically inflated relative to its apparent purpose — the server presents a full finance/prediction-market/research gateway while contributing only 4 tools to its advertised domain.

Completeness2/5

The actual Codewars surface has significant gaps: kata, user, user_authored, and user_completed are purely read-only, with no solution submission, attempt/training history, leaderboard access, or kata search by difficulty/language. Meanwhile the Pipeworx side is over-complete for a server not named for it, leaving the server's stated identity under-covered with no way to perform any write operation on the Codewars platform.