Skip to main content
Glama

Conspiracy Theory

by io.github.pipeworx-io

Remember

remember
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

A4.7/5.0
Behavior5/5

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

Annotations already indicate idempotentHint=true and non-destructive. The description adds important behavioral context: scoped by identifier, persistent for authenticated users, 24-hour retention for anonymous. No contradiction with annotations.

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?

Three well-structured sentences, front-loaded with the core purpose. No unnecessary words. Each sentence adds value.

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?

Despite no output schema, the description fully covers the tool's behavior: what is stored, scoping, persistence, and pairing with siblings. For a write-only tool, it is complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and parameter descriptions are already descriptive. The description does not add new meaning beyond the schema for the parameters, but it sets context. Baseline 3 is appropriate.

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.' It specifies the verb 'save' and the resource 'data' as key-value pairs, and distinguishes from sibling tools like recall and forget.

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?

Explicit guidance is given: 'Use when you discover something worth carrying forward... Pair with recall to retrieve later, forget to delete.' Also mentions scoping and persistence duration, providing clear when-to-use and alternatives.

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

All Conspiracy Theory toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.6/5.0
Disambiguation2/5

Several tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, discover_tools, and suggest_questions all serve route/discover/research data needs, with ask_pipeworx_beta explicitly noted as currently identical to ask_pipeworx. Polymarket tools also blur together (polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk), and ai_visibility_check vs scan_competitor_ai_presence are near-duplicates. An agent would frequently need to read long descriptions just to pick between near-equivalent entry points.

Naming Consistency3/5

The set is mostly snake_case and generally readable, with clear verbs like list_subscriptions, resolve_entity, generate_llms_txt, and validate_claim. However, conventions are mixed: brand-prefixed nouns appear (pipeworx_feedback, pipeworx_trending), one tool reverses the pattern (conspiracy_theory_generate vs generate_llms_txt), and the ask_pipeworx family follows its own scheme. The inconsistency is noticeable but does not make the names unreadable.

Tool Count2/5

32 tools is heavy, and the apparent scope is a scattered mix of general data research, prediction markets, memory, subscriptions, AI visibility, npm dependency checks, and conspiracy-theory generation. Many tools are meta-routers or aggregators that could be consolidated (e.g., the ask_pipeworx family, the polymarket family, the entity-research tools). The count feels like a growing internal toolkit rather than a deliberately scoped server.

Completeness2/5

The tools cover some complete sub-domains — memory has remember/recall/forget, subscriptions have subscribe/unsubscribe/list/recent_alerts, and data lookup has multiple verification and research paths. But the server's nominal 'Conspiracy Theory' purpose is essentially one generation tool with no save, share, history, or validation workflow, while the bulk of the surface is unrelated general-purpose data tooling. The overall offering is broad but not coherently complete for any clear stated purpose.

Resources