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by io.github.pipeworx-io

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Idempotent

Save data the agent will need to reuse later — across this conversation or across sessions. Use when you discover something worth carrying forward (a resolved ticker, a target address, a user preference, a research subject) so you don't have to look it up again. Stored as a key-value pair scoped by your identifier. Authenticated users get persistent memory; anonymous sessions retain memory for 24 hours. Pair with recall to retrieve later, forget to delete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYesMemory key (e.g., "subject_property", "target_ticker", "user_preference")
valueYesValue to store (any text — findings, addresses, preferences, notes)

TDQS

A4.9/5.0
Behavior5/5

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

Annotations indicate write operation (readOnlyHint: false), non-destructive, idempotent. Description adds key details: scoped by identifier, 24-hour retention for anonymous, persistent for authenticated. No contradiction.

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?

Multiple sentences but each adds value: purpose first, then usage, then behavioral details, then pairing. No filler or redundancy.

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 simple 2-param tool with no output schema, the description covers all necessary aspects: what it does, when to use, how it behaves, and its relationship to siblings. No gaps.

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 provides descriptions for both parameters (100% coverage). Description adds naming conventions (e.g., 'subject_property') and clarifies that value is free-form text, enhancing schema information.

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 clearly states the tool saves data for later reuse, provides concrete examples (ticker, address, preference), and distinguishes from siblings recall and forget by mentioning pairing.

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?

Explicitly says when to use: 'when you discover something worth carrying forward' and contrasts with recall/forget. Also clarifies persistence differences between authenticated and anonymous sessions.

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 clusters of tools are hard to tell apart: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all serve overlapping query paths, and the five polymarket_* tools plus bet_research cover heavily overlapping prediction-market analysis. Some pairs are nearly identical in purpose, like ai_visibility_check vs scan_competitor_ai_presence, and the descriptions must be read closely to avoid misselection.

Naming Consistency2/5

All names are snake_case, but the naming style is highly inconsistent across the set: some use verb_noun (ask_pipeworx, generate_llms_txt, resolve_entity), some are noun phrases (entity_profile, pipeworx_feedback, recent_alerts), and some use a vendor prefix without a clear verb (polymarket_edges, polymarket_edge_tracker). The pattern shifts between domain-specific prefixes (polymarket_*, pipeworx_*) and generic verbs with no predictable rule.

Tool Count2/5

32 tools is too many for a cohesive server, especially when the surface sprawls across unrelated domains: data querying, prediction markets, memory, subscriptions, npm scanning, AI visibility checks, and llms.txt generation. Many tools could be consolidated (the ask_pipeworx family, the polymarket family, the entity-comparison family), which would make the count feel more justified.

Completeness4/5

Within its apparent purpose as a broad data-and-research assistant, the tool set is fairly complete: it covers entity resolution, lookup, grounded verification, deep research, comparisons, memory CRUD, subscription lifecycle, discovery, and feedback. Minor gaps exist, such as no direct tool to fetch a record by its pipeworx:// citation URI (search_within implies fetching happens elsewhere) and no evident update operation for stored memories beyond save/delete.

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