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Glama

Chaos Index

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 provide idempotentHint=true and destructiveHint=false. Description adds key-value scoping by identifier, persistence details (authenticated vs anonymous 24hr), and pairing with other tools. 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?

Four sentences with excellent front-loading: first sentence states purpose, second gives usage guidance, third and fourth add behavioral details. No wasted words.

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?

Complete for a write-only tool with 2 parameters and no output schema. Covers purpose, timing, persistence, and relationships to siblings without 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 coverage 100% with descriptions for key and value. Description reinforces key-value pair and adds naming conventions (e.g., 'subject_property'), going 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?

Clear verb 'Save data' with resource scope 'the agent will need to reuse later'. Distinguishes from siblings 'recall' and 'forget' by stating it is for storing, while those are for retrieval and deletion.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use 'when you discover something worth carrying forward' with concrete examples (ticker, address, preference). Pairs with recall and forget. No explicit when-not-to-use, but context is 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

A3.9/5.0
Disambiguation2/5

The set contains multiple near-duplicate entry points: ask_pipeworx, ask_pipeworx_beta (explicitly identical right now), and ask_pipeworx_grounded overlap heavily, while deep_research, discover_tools, and suggest_questions all claim to be the 'call this first' tool. Also, ai_visibility_check vs scan_competitor_ai_presence and the five polymarket_* tools create boundaries an agent could easily mischoose.

Naming Consistency4/5

Most tools follow a clear snake_case verb_noun pattern (compare_entities, validate_claim, unsubscribe, search_within). Minor deviations exist — chaos_index_calculate puts the verb last, entity_profile is noun-only, and the pipeworx_ prefix is applied inconsistently (pipeworx_trending vs ask_pipeworx) — but the overall style is predictable.

Tool Count2/5

32 tools is too many for a coherent single-purpose server; the set spans data routing, prediction markets, subscriptions, memory, AI visibility, npm scanning, and llms.txt generation. It reads as a bundled suite of unrelated utilities rather than a focused tool surface.

Completeness3/5

Subdomains are individually fairly complete: subscription CRUD, memory CRUD, and the prediction-market workflow (research, edges, arbitrage, fill risk, tracking) are all covered. However, the overall domain is incoherent, and gaps exist such as no update-subscription operation and no way to modify an existing memory beyond overwriting via remember.