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Glama

Timestamp

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

A4.4/5.0
Behavior4/5

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

Adds value beyond annotations: requires OAuth, returns new id, details delivery channel behaviors (SMS cap, webhook secret one-time, auto-disable after failures). No contradiction with annotations (readOnlyHint=false, idempotentHint=true, destructiveHint=false).

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?

Moderately long but well-structured and front-loaded: purpose, requirements, then types, then delivery. Every sentence adds value, though could be slightly more compact. No waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers all important aspects: type-specific params with examples, delivery constraints, account requirement. No output schema, but mentions return of subscription id and webhook secret. Adequate for the tool's complexity.

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 description adds significant context: JSON examples for each type, detailed constraint explanations for delivery fields (e.g., phone verification, 10/day cap, webhook HMAC signing). Goes well beyond 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?

Description uses a specific verb-resource pair ('Create a proactive monitoring subscription') and states it returns a subscription id. Clearly distinguishes from sibling tools like 'list_subscriptions' and 'unsubscribe'.

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?

Explicitly states the requirement for a Pipeworx OAuth account and that anonymous/BYO cannot persist. Provides detailed type-specific parameters and delivery options. Does not explicitly say when not to use, but implied by alternatives in sibling list.

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

Many tools occupy heavily overlapping territory: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, bet_research, validate_claim, and even entity_profile/compare_entities all route questions to similar underlying data and could easily be misselected. The Polymarket suite adds another cluster of near-synonymous tools. Descriptions are detailed, but the boundaries require careful reading to keep straight.

Naming Consistency2/5

Tool names mix imperative verbs (remember, subscribe, resolve_entity, validate_claim), noun-phrase descriptors (entity_profile, recent_changes, polymarket_edges), and time-utility names (now, from_timestamp, to_timestamp, relative_time). All-lowercase snake_case is consistent, but there is no unified verb_noun or domain-prefix pattern across the set.

Tool Count2/5

35 tools is heavy and exceeds the comfortable 3-15 range, and most of them are unrelated to the server name 'Timestamp,' which adds confusion. The broad Pipeworx data scope justifies more than a tiny utility server, but the count still feels overstuffed and will burden tool selection.

Completeness3/5

For the broad data-research and prediction-market domain the set actually covers, the lifecycle is fairly complete: query, deep research, entity profiles, comparisons, claim validation, subscription management, and memory storage all have working operations. However, the surface is sprawling and includes one-off tools like generate_llms_txt and scan_dependency that do not fit any coherent domain, making completeness hard to assess and leaving a fuzzy, fragmented impression.

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