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Ecfr

by io.github.pipeworx-io

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Idempotent

Create a proactive monitoring subscription to a live-data event stream. Returns the new subscription id. Requires a Pipeworx OAuth account (anonymous + BYO cannot persist subscriptions). Supported types: "sec_8k" (8-K filings matching ticker + item codes — e.g. items:["5.02"] = officer change), "polymarket_edge" (Polymarket↔Kalshi cross-venue mispricings — params:{topic:"fed"}), "fred_series" (new FRED observations — params:{series_id:"UNRATE"}). Delivery channels: feed (always on — pull via recent_alerts or GET registry.pipeworx.io/alerts.json), and optionally email (set delivery:{email:"you@x.com"}) or sms (delivery:{sms:"+15551234567"} — phone must be verified at /account first; 10/day cap).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesSubscription type.
paramsYesType-specific filter. sec_8k: {ticker:"AAPL", items?:["5.02","1.01"]}. polymarket_edge: {topic:"fed", min_spread_bps?:500}. fred_series: {series_id:"UNRATE"}. patent_grant: {applicant:"Apple Inc."}. clinical_trial: {sponsor?:"Pfizer", condition?:"lung cancer", phase?:"PHASE3"} (sponsor or condition required).
deliveryNoOptional delivery channels in addition to the always-on persistent feed. {email:"you@x.com"} sends a templated alert per fired event. {sms:"+15551234567"} sends an SMS per event — must match the verified phone on the caller's account (verify at https://pipeworx.io/account first; 10/day cap). {webhook:"https://..."} POSTs each event JSON to your endpoint, HMAC-signed — the response includes delivery.webhook_secret (whsec_…) ONCE; verify X-Pipeworx-Signature = sha256 HMAC of "<X-Pipeworx-Timestamp>.<raw body>". Auto-disabled after 10 consecutive failing runs.

Schema Changelog

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

  1. First observed

TDQS

A3.8/5.0
Behavior1/5

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

The description states 'Returns the new subscription id,' implying each call creates a distinct subscription, which contradicts the annotation idempotentHint=true (calls with identical parameters should have no additional effect). This is a clear contradiction per the rubric, requiring a score of 1.

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 well-structured with a clear first sentence stating purpose, followed by essential details on requirements, types, and delivery. It is front-loaded and concise for the amount of information covered, though slight reorganization could improve scannability.

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?

Given the tool's complexity (multiple subscription types, delivery channels, account requirements, rate limits, webhook details) and no output schema, the description explains the return value, account prerequisites, type-specific parameters, delivery options, and post-subscription behavior thoroughly.

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?

Although schema coverage is 100%, the description adds significant value by providing concrete examples for each subscription type and detailing delivery channel caveats (e.g., phone verification, SMS daily cap, webhook auto-disable). This exceeds the baseline of 3.

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 creates a proactive monitoring subscription to a live-data event stream, specifies it returns a new subscription ID, and is distinct from sibling tools like list_subscriptions (view), unsubscribe (remove), and recent_alerts (fetch alerts).

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 provides explicit prerequisites (Pipeworx OAuth account), supported types with examples, and delivery channel options. However, it does not explicitly state when not to use this tool versus alternatives like list_subscriptions or unsubscribe, though the context is sufficient to infer.

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.

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