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Science Feeds

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

A4.5/5.0
Behavior4/5

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

Annotations already declare idempotentHint=true and destructiveHint=false. The description adds context about scope ('scoped by your identifier'), expiration (24 hours for anonymous), and pairing with recall/forget, which goes beyond 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?

Multiple sentences but each adds value. Front-loaded with purpose. No redundant information. Could be slightly more concise, but structure (purpose, usage, mechanics, pairing) is logical.

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?

No output schema, but for a write tool this is acceptable. Covers purpose, usage, persistence, and pairing with siblings. Adequately complete for an agent to use correctly.

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% with descriptions. The description adds value by giving example keys ('subject_property', 'target_ticker') and clarifying value semantics ('any text'), enhancing understanding beyond the 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's purpose ('Save data the agent will need to reuse later') and resource ('key-value pair'). It distinguishes itself from sibling tools like recall and forget by explicitly pairing with them.

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 guidance on when to use ('when you discover something worth carrying forward'), references alternatives (recall, forget), and notes authentication-based persistence differences.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Science Feeds toolsInspect
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TDQS

A4/5.0
Disambiguation2/5

ask_pipeworx, ask_pipeworx_beta (currently identical in behavior), and ask_pipeworx_grounded overlap heavily, and the six-tool Polymarket cluster (edges, arbitrage, fill_risk, edge_tracker, kalshi_spread, bet_research) requires careful reading to distinguish. Descriptions are detailed, but several tools present real selection ambiguity.

Naming Consistency4/5

Nearly all tools use snake_case with a mostly verb-first or resource-first pattern (ask_, list_, fetch_, read_, subscribe, validate_claim). Minor deviations like entity_profile and recent_changes break the verb-noun pattern slightly, but the overall naming is predictable.

Tool Count2/5

34 tools is excessive for the 'Science Feeds' name, which implies a narrow feed-reading service; only 3 tools actually relate to feeds. The rest form a broad Pipeworx grab bag (memory, npm scanning, AI visibility, prediction markets, feedback), making the set feel unfocused and overweight.

Completeness4/5

For the broad query/research domain the descriptions actually establish, coverage is strong: discovery, single lookups, grounded/refusal-safe answers, deep research, entity resolution, comparison, change feeds, claim validation, subscriptions, memory, and feedback are all present. The literal science-feed surface is thin, but the toolkit as a whole has few dead ends.

Resources