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Glama

Bis

by io.github.pipeworx-io

Recent Changes

recent_changes
Read-onlyIdempotent

"What's new with X" / "latest on Y" / "what happened to Z this week / month / quarter" / "updates on Acme" / "news on Tesla recently" / "what's happening with Apple" — change feed for a company in the last N days/weeks/months in ONE parallel call. Fans out to SEC EDGAR (filings since since), GDELT→GNews fallback (news mentions in window — GDELT preferred, GNews when rate-limited or 5xx), USPTO (patents granted; PatentsView API sunset May 2025 so this soft-fails until reactivated). since accepts ISO date ("2026-04-01") or relative shorthand ("7d", "30d", "3m", "1y"). Returns structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs. Use entity_profile instead when you want the static profile (filings + fundamentals + LEI + patents) regardless of window.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesEntity type. Only "company" supported today.
sinceYesWindow start — ISO date ("2026-04-01") or relative ("7d", "30d", "3m", "1y"). Use "30d" or "1m" for typical monitoring.
valueYesTicker (e.g., "AAPL") or zero-padded CIK (e.g., "0000320193").

Schema Changelog

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

  1. First observed

TDQS

A5/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds rich behavioral detail: fans out to multiple APIs, GDELT→GNews fallback, USPTO soft-fail due to PatentsView sunset, and the 'ONE parallel call' behavior. It also discloses the return structure, which is beyond what annotations provide.

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 information-dense but every sentence earns its place: intent examples, source list, fallback logic, parameter syntax, return format, and an explicit alternative. There is no filler or repetition; the opening examples immediately ground the tool's purpose.

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?

For a 3-parameter tool with no output schema, the description is remarkably complete. It specifies return shape (changes[] grouped by source, total_changes, citation URIs), behavior under edge cases (USPTO soft-fail), and the path to fetch static profiles. Nothing essential is missing.

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% (all three parameters are described), so the baseline is 3. The description goes further by explaining `since` with both ISO and relative shorthand examples ('2026-04-01', '7d', '3m'), interpreting `value` as ticker or CIK, and clarifying `type` is only 'company'. This adds contextual meaning that helps the agent select correct values.

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 concrete user intents ('What's new with X', 'latest on Y') and then precisely defines the tool as a change feed for a company over a time window in a single parallel call. It lists specific data sources (SEC EDGAR, GDELT/GNews, USPTO) and explicitly differentiates from the sibling tool entity_profile, making its purpose unmistakable and distinct.

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 explicitly tells when to use the tool (for recent updates/news on a company) and when not to (use entity_profile for static profile). It also provides fallback logic (GDELT preferred, GNews when rate-limited/5xx) and parameter usage guidance for `since`. This is clear, actionable context with an explicit alternative.

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

A3.9/5.0
Disambiguation3/5

Most tools have carefully written distinctions, but several overlap in purpose: ask_pipeworx versus ask_pipeworx_beta are currently functionally identical, and ask_pipeworx, deep_research, validate_claim, and the Polymarket research tools all sit on the same factual-question axis. The long descriptions help an agent choose, but the set still has multiple ambiguous boundaries.

Naming Consistency3/5

Names are uniformly snake_case and mostly readable, with clear prefix families like pipeworx_*, polymarket_*, and ask_pipeworx*. However, the verb-noun pattern is inconsistent: many tools are noun phrases (entity_profile, recent_alerts, polymarket_edges) and some are bare verbs (remember, recall, forget), so the naming is not predictable across the full set.

Tool Count2/5

35 tools is well above the 25-tool threshold and feels like an organic platform dump rather than a curated server. The broad data-platform scope partly justifies the number, but the presence of near-duplicate entry points and one-off utilities (generate_llms_txt, ai_visibility_check, scan_dependency) makes the set feel bloated rather than cohesive.

Completeness4/5

For a read-heavy data/research platform the surface is unusually complete: discovery, single-lookup, grounded-answer, deep-research, entity resolution, comparison, change-tracking, subscriptions, memory, and feedback are all covered. Missing write/execution capabilities like placing trades or modifying BIS flows are reasonable absences for this kind of server; the main gap is a dedicated historical/trend utility beyond the general router.

Resources