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Recall project context

recall
Read-only

One-call semantic + full-text recall over the graph — a ranked bundle of the decisions, tasks, risks, and documents most relevant to a question or topic. The default way to load context before acting; reach for search only for an exact-term or document-scoped lookup.

Input Schema

NameRequiredDescriptionDefault
depthNoBFS depth from seeds (default 1, max 3).
questionYesNatural-language question or topic — e.g. 'help me with monetization' or 'what's the state of auth?'. Embedded for semantic (meaning) search AND tokenized for keyword search; both seed sets are unioned, walked, and returned as one ranked neighborhood.
seed_limitNoCap on seed nodes from each channel (default 10).
max_entriesNoCap on returned nodes (default 30, max 100).
project_slugYesProject slug, e.g. "acme-app" — list(what="projects") returns yours.
hub_edge_limitNoPer-hub edge follow cap (default 12).

Output Schema

NameRequiredDescriptionDefault
dataYesThe action-specific result returned by Stele.
actionYesThe action that produced this result.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
    • removedInput schema / additionalProperties
      Removed value: -false
    • changedOutput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
    • changedOutput schema / properties / data / additionalProperties
      Previous value: -trueNew value: +{}
  2. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds real behavioral context beyond that: both retrieval channels are unioned, walked, and merged into one ranked result, which tells the agent what a call actually does. It stops short of noting cost/latency of the graph walk, so not a 5.

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?

Two sentences, both front-loaded: capability first, routing rule second. There is no filler and every clause carries information an agent needs at selection time.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With six parameters, full schema coverage, an output schema, and explicit annotations, the description fills the remaining gaps — purpose, mechanism, and sibling routing. It omits any mention of what happens on an empty or sparse graph, but that is a minor residual against otherwise rich structured data.

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 description coverage is 100%, so the schema already documents depth, seed_limit, max_entries, and hub_edge_limit in detail. The description only alludes to 'a question or topic' and adds no format or tuning guidance beyond what the schema provides. Baseline 3 applies.

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?

States a specific mechanism and resource: 'one-call semantic + full-text recall over the graph' returning 'a ranked bundle of the decisions, tasks, risks, and documents.' It also explicitly contrasts itself with the sibling `search`, so an agent can distinguish the two without opening either schema.

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?

Gives both sides of the routing decision: 'The default way to load context before acting' for this tool, and 'reach for `search` only for an exact-term or document-scoped lookup' for the alternative. The selection condition is explicit, not inferred.

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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