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Ecfr

by io.github.pipeworx-io

Ask Pipeworx — Grounded

ask_pipeworx_grounded
Read-onlyIdempotent

Hallucination-resistant answer mode for high-stakes reads. Same routing as ask_pipeworx — picks the right tool from 5,798 across 1517 sources, fills arguments, fetches the data — then EXTRACTS the answer using ONLY what the tool result contains. Returns {answer, evidence (verbatim quote), confidence, source, fetched_at, refusal_reason:null} on success, OR an explicit refusal {answer:null, refusal_reason:"not_in_source"|"no_tool_match"|"tool_error"|"data_truncated"|"llm_error"} when the data doesn't directly answer. Use whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts (financial verdicts, legal claims, medical lookups, public statements). Costs one extra LLM call vs ask_pipeworx — prefer ask_pipeworx for casual lookups.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoAlias for question.
textNoAlias for question.
inputNoAlias for question.
queryNoAlias for question.
promptNoAlias for question.
questionYesYour question in natural language. Accepts query, q, prompt, text, input as aliases.

Schema Changelog

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

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

The description adds substantial behavior beyond the readOnly/openWorld/idempotent annotations: exact return shape on success, explicit refusal reasons with enum values, the guarantee that answers are extracted only from tool results, and the extra LLM call cost. It fully discloses the tool's safety and failure behavior.

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?

The description is dense but every sentence earns its place: purpose, routing mechanism, success/refusal return shapes, when to use, and cost tradeoff. The most important differentiator is front-loaded, and the structure flows naturally from behavior to usage guidance.

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 compensates by enumerating the success payload and refusal reasons. It covers invocation context, safety constraints, routing behavior, and the cost/selection tradeoff. Nothing an agent needs to decide whether to call this tool and interpret its response is missing.

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?

The input schema covers 100% of parameter meaning, including the question field and its aliases, so the description does not need to repeat parameter details. The description adds contextual value by explaining that the tool routes, fills arguments, and fetches data, but it adds no new semantic detail about the single question parameter beyond what the schema already documents.

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 opens with a specific, differentiating purpose: a hallucination-resistant answer mode for high-stakes reads. It explains the same routing as ask_pipeworx but explicitly distinguishes the grounded variant by the extraction constraint and refusal behavior, making sibling differentiation immediate.

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?

The description gives explicit when-to-use guidance: any time an answer will be quoted, cited, or acted on and facts must not be invented, with concrete high-stakes examples. It also names the alternative for casual lookups and gives the cost tradeoff, so an agent can route between siblings confidently.

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 have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-duplicates (beta is currently identical), and ai_visibility_check vs scan_competitor_ai_presence plus deep_research vs ask_pipeworx create real selection ambiguity. Some clusters like the memory trio and CFR read tools are distinct, but the overall set is confusing.

Naming Consistency3/5

Most tools use snake_case and many follow a verb_noun pattern (search_regulations, generate_llms_txt, validate_claim), but noun-first names (entity_profile, title_structure, ai_visibility_check) and prefix families (polymarket_*, pipeworx_*) break the pattern. The conventions are mixed but still readable and mostly predictable.

Tool Count2/5

35 tools is heavy for any single server, and the bulk of them (Polymarket betting, memory, AI visibility, npm scanning, subscriptions) are unrelated to the server's 'Ecfr' name, which suggests a narrow regulatory focus. This is a kitchen-sink scope, making the count feel bloated rather than well-scoped.

Completeness3/5

The eCFR-specific surface is thin — list_titles, search_regulations, get_section_text, and title_structure cover basic read/search but lack version history, update tracking, or agency-level navigation. Other mini-domains (data lookup, polymarket, subscriptions, memory) are individually fairly complete, but the absence of a unified purpose leaves clear gaps overall.

Resources