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Glama

Tradier

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?

Annotations declare the operation read-only/idempotent/non-destructive; description adds substantial behavior: structured XBRL fast path, automatic fallback to grounded pipeline, exact percent-delta math, verdict vocabulary, citation format, and the crucial could_not_verify vs unsupported distinction with verification_error{stage,detail}. This goes well beyond annotation hints.

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 typical but every section earns its place: triggers, usage rule, two execution paths, return contract, and caller warning. It is front-loaded with examples and structured by function, though a heading or shorter final sentence could tighten it.

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 having no output schema, the description fully specifies the return value (verdict choices, grounded/structured value, citation, reasoning) and failure semantics. It also covers both input params, the tolerance override, and the unsupported vs could_not_verify distinction, making it self-sufficient for a high-complexity tool.

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 already documents both parameters with 100% coverage, so baseline is 3. The description adds meaning by explaining tolerance_pct's role in hallucination detection (1–2) and its default/cap, and by clarifying that claim is free-form natural language with examples. This extra context justifies a 4.

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 explicitly frames the tool as claim verification with trigger phrases ('Is it true that…', 'fact check'), specifies a concrete resource (authoritative sources), and distinguishes it from sibling research/ask tools by focusing on true/false judgment with a verdict. The two-path description (SEC EDGAR vs grounded) further pins down scope.

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?

Gives an explicit use condition ('Use whenever the agent needs to check whether something a user said is factually correct') and differentiates handling by claim type (company-financial vs other). It does not name specific sibling tools to avoid, but the trigger-based guidance and edge-case instructions ('could_not_verify... not evidence') give clear operational direction.

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

A3.7/5.0
Disambiguation2/5

Multiple tools share overlapping purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical variants, and the five polymarket_* tools cover heavily overlapping territory. An agent must read lengthy descriptions to distinguish between them, and pairs like validate_claim vs ask_pipeworx_grounded or discover_tools vs suggest_questions have fuzzy boundaries.

Naming Consistency2/5

Naming is wildly inconsistent: verb_noun (compare_entities, discover_tools), bare verbs (forget, remember, subscribe), noun phrases (entity_profile, recent_alerts, pipeworx_feedback), prefixed families (tradier_*, polymarket_*) and suffixed variants (ask_pipeworx_beta, ask_pipeworx_grounded). There is no single predictable convention across the set.

Tool Count2/5

34 tools is far beyond the 15-25 heavy range, and the count is inflated by near-duplicates like ask_pipeworx/ask_pipeworx_beta and five polymarket edge tools. The server mixes several unrelated domains (Tradier quotes/options, Pipeworx research, Polymarket analysis, memory, subscriptions, web utilities), making the scope feel unbounded.

Completeness2/5

For a server named Tradier, having only quote and option-chain endpoints is a significant gap—no historical data, account, positions, or order execution. The Pipeworx/Polymarket side is more complete, but the inclusion of unrelated utilities like generate_llms_txt and scan_dependency means no single domain is fully served.

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