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Udbud Dk

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

A4.5/5.0
Behavior4/5

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

Beyond annotations (readOnlyHint=false, idempotentHint=true, etc.), the description adds critical behavioral details: requires OAuth account, delivery channel constraints (email verification, SMS 10/day cap, webhook HMAC signing), and that webhook is auto-disabled after 10 consecutive failures. No contradictions.

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 comprehensive but somewhat lengthy (approx. 200 words). It is well-structured with bullet points and examples, and the main purpose is front-loaded. Could be slightly more succinct without losing clarity.

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 (3 params, nested objects, multiple subscription types, delivery options), the description covers all necessary aspects: purpose, requirements, type-specific filters, delivery channels with verification and rate limits, and return value. No output schema but return of subscription id is stated.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, but the description adds significant value by providing concrete examples for each type and params (e.g., sec_8k items codes, polymarket_edge topic, fred_series series_id) and clarifying constraints (e.g., clinical_trial requires sponsor or condition). This goes well beyond the schema descriptions.

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 uses a specific verb 'Create' and identifies the resource as a 'proactive monitoring subscription' to a 'live-data event stream'. It distinguishes from sibling tools like list_subscriptions, recent_alerts, and unsubscribe by focusing on creation and return of subscription id.

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 clearly states the tool is for creating subscriptions and lists requirements (Pipeworx OAuth account) and supported types. While it doesn't explicitly state when not to use, the context of sibling tools provides cues; e.g., for listing use list_subscriptions.

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

A3.8/5.0
Disambiguation2/5

Several tools form near-overlapping clusters: ask_pipeworx and ask_pipeworx_beta are explicitly identical in behavior, while ask_pipeworx, ask_pipeworx_grounded, and deep_research have overlapping scopes. The five polymarket tools also share a common prediction-market domain and could be confused despite detailed descriptions. Some boundaries between 'meta' tools such as discover_tools, suggest_questions, and ask_pipeworx are also fuzzy.

Naming Consistency3/5

The majority of tools use lowercase snake_case and many follow a verb_noun pattern (ask_pipexors, search_within, generate_llms_txt, destroy_tools), which is readable. However, there are inconsistent orderings like ai_visibility_check and dk_tender_search, plus several one-word verb tools (remember, forget, recall) alongside noun_verb forms. So the style is mostly regular but does not follow a single consistent pattern.

Tool Count2/5

34 tools is very ot heavy for a general-purpose data platform, but the server name 'Udbud Dk' implies a narrow Danish tender scope. Only 3 of the 34 tools actually concern Danish procurement, while the rest form a broad question-answering, prediction-market, subscription, and memory platform. The count feels bloated and mismatched relative to the apparent server focus.

Completeness3/5

For the broad data domain, the server covers a wide range: lookup, grounded answers, entity resolution, fact-checking, company profiles, comparisons, change feeds, polymarket opportunities, subscriptions, and memory. But relative to the Danish tender scope implied by the server name, only search/detail/recent exist and missing functionality such as saved searches or notifications for new notices. There are also some odd gaps such as no-direct citation-lookup tool, but the generous question-answering tools compensate.

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