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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?

Discloses key behavioral details beyond annotations: key-value scoping by identifier, persistence differences for authenticated vs. anonymous users (24-hour retention). 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?

Efficiently structured: purpose, usage, technical details in 3-4 sentences. No redundancy, every 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?

Fully addresses the tool's function, scope, and edge cases given its simplicity (2 params, no output schema). No gaps remain.

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 covers 100% of parameters with descriptive examples. Description adds usage context but no additional meaning beyond schema; 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 saves data for reuse, with specific examples like 'resolved ticker' and 'user preference'. It distinguishes from sibling tools 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?

Explicitly describes when to use ('when you discover something worth carrying forward') and mentions paired tools (recall, forget), providing clear context for selection.

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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Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.8/5.0
Disambiguation2/5

Many tools overlap heavily: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical variants (beta currently identical), and the set includes five-plus prediction-market tools (polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread, bet_research) with fuzzy boundaries. Long descriptions help, but an agent selecting among them would frequently struggle to pick the right one.

Naming Consistency3/5

Names are uniformly lowercase snake_case, but the pattern is inconsistent: verb_first names (search_samples, validate_claim, resolve_entity) mix with noun-style names (entity_profile, pipeworx_trending, polymarket_arbitrage) and bare imperatives (remember, recall, forget, subscribe). It is readable, but there is no predictable verb_noun convention across the set.

Tool Count2/5

33 tools is well over the coherent range, and the count is especially inflated because the server is named Biosamples yet only two tools (search_samples, get_sample) actually belong to that domain. The remaining 31 tools are an unrelated mix of Pipeworx research, prediction-market, memory, and subscription utilities, including redundant variants.

Completeness2/5

For the stated Biosamples purpose, only search and retrieve exist—no submission, update, or batch operations—so the domain surface is a read-only fragment. For the broader accidental scope of the other tools, the set is a grab bag with no coherent lifecycle, leaving significant gaps regardless of which domain is considered primary.