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Asana

by io.github.pipeworx-io

Compare Entities

compare_entities
Read-onlyIdempotent

"Compare X and Y" / "X vs Y" / "X versus Y" / "which is bigger / better / larger / more profitable" / "rank these companies" / "head to head" — side-by-side comparison of 2–5 companies or drugs in ONE parallel call. ALWAYS PREFER over sequential single-pack lookups when comparing entities. type="company" pulls LATEST 10-K revenue + net income + cash + long-term debt from SEC EDGAR/XBRL (off-calendar fiscal years handled correctly — AAPL Sep, NVDA Jan, etc.). type="drug" pulls FAERS adverse-event counts, FDA approval counts, active trial counts. Results sorted by primary metric so "largest" / "most" / "biggest" reads off the top of the response. Returns paired data + pipeworx:// citation URIs per entity. Replaces 8–15 sequential lookups.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesEntity type: "company" or "drug".
valuesYesFor company: 2–5 tickers/CIKs (e.g., ["AAPL","MSFT"]). For drug: 2–5 names (e.g., ["ozempic","mounjaro"]).

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, and open-world hints. Description adds valuable behavioral details: data sources (SEC EDGAR/XBRL, FAERS, FDA), metrics returned, sorting by primary metric, citation URIs, and parallel execution. 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is dense but efficient, front-loaded with trigger phrases and usage guidance, followed by datasource and behavior details. No repetition of schema or annotations.

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 tool with 2 parameters and no output schema, description fully covers purpose, data sources, sorting, return format (paired data + citations), and replacement of many lookups. All necessary context present.

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?

Schema coverage is 100%, baseline 3. Description enriches by explaining what each type enum value means (pulls specific data), and provides examples for values parameter (tickers/CIKs for company, drug names). Adds meaning beyond schema.

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 performs side-by-side comparison of 2-5 companies or drugs, with specific verb 'compare' and resource 'entities'. It distinguishes from single-entity lookups via explicit preference statement.

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?

Provides explicit trigger phrases, states when to use (comparing entities), and strongly advises against sequential single-pack lookups. Implicitly excludes single-entity use cases, making usage boundaries clear.

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

B3.3/5.0
Disambiguation2/5

The tool set mixes Asana project management tools with a large number of Pipeworx data retrieval tools. Within the Pipeworx subset, tools like ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded have overlapping purposes, and multiple prediction market tools exist (e.g., polymarket_arbitrage, polymarket_edges). This creates ambiguity and potential for misselection.

Naming Consistency2/5

Tool names lack a consistent pattern. Some use 'asana_' prefix, others use descriptive phrases (e.g., 'compare_entities', 'generate_llms_txt'), and some are single verbs (e.g., 'forget', 'remember'). Mix of different conventions leads to unpredictability.

Tool Count2/5

37 tools is high for a server named 'Asana', yet only 6 tools are Asana-specific. The majority are Pipeworx tools unrelated to Asana. This overloading makes the server feel bloated and off-purpose.

Completeness2/5

For Asana functionality, the set is incomplete: missing update/delete task, project management features, etc. The Pipeworx tools are extensive but irrelevant to the server's stated purpose, leaving the Asana workflow with notable gaps.

Resources