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recall

Read-only

Retrieve relevant past feedback, memories, and prevention rules for current tasks to apply previous learnings and avoid repeating mistakes.

Instructions

Recall relevant past feedback, memories, and prevention rules for the current task. Call this at the start of any task to inject past learnings into the conversation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesDescribe the current task or context to find relevant past feedback
limitNoMax memories to return (default 5)
repoPathNoOptional repository path for structural impact analysis on coding tasks

Implementation Reference

  • The `buildRecallResponse` function implements the logic for the "recall" tool, which constructs a context pack based on a query, analyzes code graph impact, and formats the response.
    function buildRecallResponse(args = {}) {
      const limit = checkLimit('recall');
      ensureContextFs();
      const pack = constructContextPack({
        query: args.query || '',
        maxItems: Number(args.limit || 5),
      });
      const impact = analyzeCodeGraphImpact({
        intentId: null,
        context: args.query || '',
        repoPath: args.repoPath,
      });
      const section = formatCodeGraphRecallSection(impact);
      let text = section
        ? `${formatContextPack(pack)}\n\n${section}`
        : formatContextPack(pack);
    
      if (!limit.allowed) {
        text += '\n\n---\n';
        text += 'Upgrade to Context Gateway for unlimited recall, shared workflow memory, and hosted rollout.\n';
        text += 'Hosted API: https://rlhf-feedback-loop-production.up.railway.app\n';
        text += 'Pro pack: https://rlhf-feedback-loop-production.up.railway.app/checkout/pro';
      }
    
      return toTextResult(text);
    }
Behavior4/5

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

The annotation 'readOnlyHint: true' already indicates this is a safe read operation. The description adds value by specifying behavioral context: it recalls 'past feedback, memories, and prevention rules' and is intended for use 'at the start of any task,' which helps the agent understand its role in workflow sequencing. However, it doesn't detail aspects like rate limits or authentication needs, so it's not a perfect 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?

The description is two sentences, front-loaded with the core purpose and followed by usage guidance. Every word contributes to understanding the tool's role, with no wasted text or redundancy, making it highly efficient and well-structured.

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?

Given the tool's complexity (3 parameters, 1 required), annotations (readOnlyHint), and lack of output schema, the description is mostly complete. It clearly states the purpose and usage, but could benefit from mentioning what the output looks like (e.g., format of recalled items) since there's no output schema. However, it covers essential context for a read operation.

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 all parameters ('query', 'limit', 'repoPath') with descriptions. The description does not add any additional meaning or examples beyond what the schema provides, such as clarifying how 'query' should be formulated or when 'repoPath' is necessary. Thus, it meets the baseline for high schema coverage.

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 specific action ('Recall') and resources ('relevant past feedback, memories, and prevention rules'), and distinguishes its purpose from siblings by specifying it should be called 'at the start of any task' to 'inject past learnings into the conversation.' This is precise and differentiates it from other tools like 'capture_feedback' or 'prevention_rules.'

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?

The description provides explicit guidance on when to use this tool: 'Call this at the start of any task to inject past learnings into the conversation.' This clearly indicates the timing and context for usage, distinguishing it from alternatives that might capture or manage feedback rather than recall it.

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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