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Glama

Wayback

by io.github.pipeworx-io

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.

Schema Changelog

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

  1. Changed1 schema field changed
    • addedInput schema / properties / tolerance_pct
      Added value: +{
+  "description": "Max 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.",
+  "type": "number"
+}
  2. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Goes beyond annotations by explaining the crucial distinction between could_not_verify (check did not happen due to LLM/source failure) and unsupported (no source coverage), including that could_not_verify must not be shown as evidence. Discloses return structure (verdict, actual value, citation, reasoning) and error semantics. No contradiction with readOnlyHint/openWorldHint.

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 longer than average but densely packed with useful routing, error-handling, and replacement guidance. Each section contributes value, though a few phrases (e.g., 'grounded pipeline — routed to the right live source') are slightly redundant with earlier mentions. Overall well-structured and front-loaded with the core purpose.

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?

Despite no output schema, the description fully explains return values (verdict types, actual value with citation, reasoning) and error states (could_not_verify with verification_error, unsupported). It accounts for the tool's complexity by covering two distinct pipelines and the tolerance semantics. Given its complexity, this is a complete and self-sufficient description.

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%, so the baseline is 3. The description provides claim examples but does not add meaningful semantic detail beyond the schema. The tolerance_pct parameter is explained in the schema (and the description implies its existence through grading logic) but not elaborated in the description itself.

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 claim verifier with specific trigger examples ("Is it true that…", "fact check"). It uniquely identifies the resource (factual claims) and distinguishes itself from sibling tools, which are unrelated to claim verification.

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?

States explicitly when to use ("Use whenever the agent needs to check whether something a user said is factually correct") and provides routing guidance between the SEC EDGAR path for company-financial claims and the grounded pipeline for all other claims. Also notes it replaces 4–6 sequential calls, clarifying efficiency.

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

Several tool clusters overlap heavily: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical in purpose, and the five polymarket_* tools all target prediction-market analysis. The presence of a broad Pipeworx data layer alongside Wayback-specific tools under one server name further blurs boundaries.

Naming Consistency3/5

Most tools use snake_case, but the pattern varies: many follow verb_noun (get_snapshot, list_snapshots, resolve_entity, validate_claim), while others are noun_noun (entity_profile, polymarket_edges, pipeworx_feedback, bet_research). Suffixes like _beta and _grounded are used inconsistently, and some names are long and descriptive while others are terse.

Tool Count2/5

34 tools is far more than what a Wayback Machine server should need, and most tools (Pipeworx data queries, prediction-market analysis, memory, subscriptions) have nothing to do with the Wayback Machine. The server's stated purpose appears narrow, but the tool set is bloated with unrelated functionality.

Completeness2/5

For the Wayback Machine domain, only three tools are relevant (get_capture_count, get_snapshot, list_snapshots), and obvious operations like saving/archiving a URL, comparing snapshots, or handling deleted captures are missing. The Pipeworx-related tools are broad but not clearly aligned with the Wayback theme, so the core purpose is under-served.

Resources