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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

A4.5/5.0
Behavior5/5

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

Beyond the annotations, the description discloses important behavior: memory is scoped by the agent identifier, authenticated users get persistent memory, and anonymous sessions retain it for 24 hours. It also frames the tool as a storage operation paired with recall/forget, adding meaningful context beyond idempotentHint.

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 focused sentences, front-loaded with the core action, followed by usage guidance, storage details, and companion-tool references. No filler or redundant restatement of the tool name.

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 two-parameter memory tool, the description covers purpose, when to use it, persistence semantics, scoping, and related tools. Combined with helpful annotations, the description is complete enough for an agent to select and invoke it correctly.

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?

The input schema already describes both parameters fully (100% coverage), including key and value format examples. The description reinforces that the tool stores key-value pairs but does not add further parameter-level details beyond what the schema provides.

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 opens with 'Save data the agent will need to reuse later', giving a specific verb and resource. It also explains the key-value storage model and explicitly mentions recall and forget, which distinguishes it from sibling retrieval/deletion tools.

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?

It provides clear usage context: 'Use when you discover something worth carrying forward' and gives concrete examples. It names recall and forget as complementary tools, but does not explicitly state when not to use remember.

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
Disambiguation4/5

Most tools target distinct purposes (e.g., ask_pipeworx vs. get_repo vs. validate_claim), but there is some overlap between ask_pipeworx and ask_pipeworx_grounded, and between bet_research and polymarket_edges. Overall, an agent can generally distinguish them.

Naming Consistency2/5

Tool names lack a consistent pattern: some are verb_noun (search_repos, get_user), others are noun_verb (entity_profile), and many are compound descriptor phrases (polymarket_arbitrage, scan_dependency). This mixed convention makes the set feel disjointed.

Tool Count2/5

38 tools is excessive for a server named 'Github', especially since many tools (e.g., ai_visibility_check, bet_research) are unrelated to GitHub functionality. The count would be appropriate for a broader 'Pipeworx' server but not for a focused GitHub server.

Completeness2/5

The GitHub-relevant tools are limited to read-only operations (get_repo, list_commits, etc.), lacking essential actions like creating/updating repos, issues, or pull requests. The inclusion of numerous non-GitHub tools does not compensate for these gaps.