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Recall

recall
Read-onlyIdempotent

Retrieve a value previously saved via remember, or list all saved keys (omit the key argument). Use to look up context the agent stored earlier — the user's target ticker, an address, prior research notes — without re-deriving it from scratch. Scoped to your identifier (anonymous IP, BYO key hash, or account ID). Pair with remember to save, forget to delete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyNoMemory key to retrieve (omit to list all keys)

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already indicate readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description confirms these by stating it retrieves saved values and lists keys. It adds behavioral context about scoping to an identifier (anonymous IP, BYO key hash, or account ID), which is not in 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 sentences convey functionality, usage examples, and scoping without waste. The first sentence front-loads the core action. Every sentence adds unique 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?

For a simple one-parameter read-only tool with full annotation coverage, the description covers what, when, how (parameter behavior), and context (scoping, partnering tools). No information is missing for effective use.

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?

The input schema has 100% coverage with a description for the single parameter 'key'. The description explains omitting key lists all keys and relates key to previously saved values. This adds meaningful context beyond the schema's basic description.

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 explicitly states the tool retrieves a value saved via remember or lists all keys when omitted. It uses specific verbs ('retrieve', 'list') and resources ('value', 'keys'). It distinguishes from sibling tools like remember (save) and forget (delete) by mentioning them as partners.

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?

The description provides concrete examples of when to use the tool (look up target ticker, address, research notes) and implies not to use it for re-deriving context. It guides pairing with remember and forget. However, it lacks explicit 'do not use when' statements.

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

A3.6/5.0
Disambiguation2/5

Several tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta (explicitly identical today), ask_pipeworx_grounded, deep_research, and validate_claim all route factual questions through similar pipelines. The polymarket_* cluster also blurs together, with arbitrage, edges, fill_risk, kalshi_spread, and bet_research all analyzing prediction-market mispricings from different angles.

Naming Consistency3/5

All names use consistent snake_case, but the verb/noun pattern is mixed: some are verb-first (compare_entities, generate_llms_txt, validate_claim), others noun-first (polymarket_edges, entity_profile, ai_visibility_check), and some are bare product names (ask_pipeworx, pipeworx_trending). Readable overall, but no single predictable convention.

Tool Count2/5

34 tools is far too many for a coherent server, especially since the server is named 'Sgd' but only 3 tools relate to yeast genetics. The remaining 31 tools span data lookup, prediction markets, memory, subscriptions, npm scanning, and llms.txt generation—an unfocused grab bag that should be split into multiple servers.

Completeness2/5

As an SGD yeast-genome server, the surface is thin: search, get_gene, and get_gene_go cover basic lookup but miss sequences, interactions, strains, homologs, and other standard SGD data. As a general data utility, the collection is broad but incoherent, with several one-off tools (generate_llms_txt, scan_dependency) that have no connection to the rest.