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Bungie

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").

TDQS

A4.9/5.0
Behavior5/5

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

Annotations indicate a read-only, idempotent, non-destructive tool. The description adds detailed behavioral traits: parallel calls to multiple sources (SEC EDGAR, GDELT/GNews, USPTO), fallback mechanism (GNews when rate-limited), soft-failure for USPTO, date format acceptance, and return structure (changes grouped by source with citations). This goes well beyond the annotations.

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 and front-loaded with example queries, but it is somewhat lengthy due to the inclusion of multiple source details and fallback behavior. While informative, it could be slightly more concise without losing key information.

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 data sources, fallback, date variants, soft-failure), the description covers all necessary context. It mentions the return format (changes[], total_changes, citations) and limitations (USPTO soft-fail), making it complete without an output schema.

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%, providing a baseline of 3. The description significantly adds value by explaining the 'since' parameter with examples ('2026-04-01', '7d', '30d', '3m', '1y'), clarifying that 'type' only supports 'company,' and detailing that 'value' can be a ticker or zero-padded CIK. This goes 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?

The description clearly states the tool's purpose as a 'change feed for a company in the last N days/weeks/months in ONE parallel call.' It lists illustrative queries like 'What's new with X' and 'latest on Y,' and explicitly distinguishes itself from the sibling tool 'entity_profile,' which handles static profiles.

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 guides when to use this tool by stating 'Use entity_profile instead when you want the static profile.' It also implies usage for dynamic change feeds and provides examples of appropriate queries.

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

C2.7/5.0
Disambiguation3/5

The tool set mixes Destiny 2 game tools with a large suite of general data querying tools from Pipeworx. Within the data querying subset, tools like ask_pipeworx, ask_pipeworx_grounded, and deep_research have overlapping purposes, making it hard for an agent to distinguish which to use. The Destiny tools are more distinct, but overall, the set has noticeable ambiguity.

Naming Consistency2/5

Tool names are highly inconsistent, mixing single-word names (character, clan), snake_case (ask_pipeworx, deep_research), and compound names with underscores (polymarket_arbitrage, scan_dependency). There is no uniform verb_noun or other predictable pattern, making it difficult for an agent to infer functionality from the name alone.

Tool Count2/5

With 43 tools, the server is bloated for its stated name 'Bungie'. Many tools are unrelated to Bungie (e.g., Pipeworx data tools, Polymarket tools), suggesting the server aggregates multiple domains without clear scoping. The tool count is too high for a coherent set focused on a single service.

Completeness2/5

For the Bungie game domain, the set is fairly complete (characters, clans, stats). However, the inclusion of numerous unrelated tools (financial, economic, prediction market) fragments completeness. The server lacks a clear domain, leaving gaps in both the Bungie-specific and the general data querying aspects when considered as a unified set.

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