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twining_decide

Record development decisions with full rationale, alternatives considered, and traceability. Creates structured decision records and cross-posts to a shared blackboard for team coordination.

Instructions

Record a decision with full rationale, alternatives considered, and traceability. Creates a decision record and cross-posts to the blackboard.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYesDecision domain (e.g., "architecture", "implementation", "testing")
scopeYesWhat part of the codebase this affects
summaryYesOne-line decision statement
contextYesSituation that prompted this decision
rationaleYesReasoning for the choice
constraintsNoWhat limited the options
alternativesNoAlternatives that were considered
depends_onNoIDs of prerequisite decisions
supersedesNoID of decision this replaces
confidenceNoConfidence level (default: "medium")
reversibleNoWhether this decision is easily reversible (default: true)
affected_filesNoFile paths affected by this decision
affected_symbolsNoFunction/class names affected
agent_idNoIdentifier for the deciding agent (default: "main")
commit_hashNoGit commit hash to associate with this decision

Implementation Reference

  • Tool registration for "twining_decide" in `src/tools/decision-tools.ts`. It takes a comprehensive input schema of decision details and calls the `engine.decide(args)` method to perform the action.
    server.registerTool(
      "twining_decide",
      {
        description:
          "Record a decision with full rationale, alternatives considered, and traceability. Creates a decision record and cross-posts to the blackboard.",
        inputSchema: {
          domain: z
            .string()
            .describe(
              'Decision domain (e.g., "architecture", "implementation", "testing")',
            ),
          scope: z
            .string()
            .describe("What part of the codebase this affects"),
          summary: z.string().describe("One-line decision statement"),
          context: z.string().describe("Situation that prompted this decision"),
          rationale: z.string().describe("Reasoning for the choice"),
          constraints: z
            .array(z.string())
            .optional()
            .describe("What limited the options"),
          alternatives: z
            .array(
              z.object({
                option: z.string().describe("Alternative option considered"),
                pros: z
                  .array(z.string())
                  .optional()
                  .describe("Advantages of this alternative"),
                cons: z
                  .array(z.string())
                  .optional()
                  .describe("Disadvantages of this alternative"),
                reason_rejected: z
                  .string()
                  .describe("Why this alternative was rejected"),
              }),
            )
            .optional()
            .describe("Alternatives that were considered"),
          depends_on: z
            .array(z.string())
            .optional()
            .describe("IDs of prerequisite decisions"),
          supersedes: z
            .string()
            .optional()
            .describe("ID of decision this replaces"),
          confidence: z
            .enum(["high", "medium", "low"])
            .optional()
            .describe('Confidence level (default: "medium")'),
          reversible: z
            .boolean()
            .optional()
            .describe("Whether this decision is easily reversible (default: true)"),
          affected_files: z
            .array(z.string())
            .optional()
            .describe("File paths affected by this decision"),
          affected_symbols: z
            .array(z.string())
            .optional()
            .describe("Function/class names affected"),
          agent_id: z
            .string()
            .optional()
            .describe('Identifier for the deciding agent (default: "main")'),
          commit_hash: z
            .string()
            .optional()
            .describe("Git commit hash to associate with this decision"),
        },
      },
      async (args) => {
        try {
          const result = await engine.decide(args);
          return toolResult(result);
        } catch (e) {
          if (e instanceof TwiningError) {
            return toolError(e.message, e.code);
          }
          return toolError(
            e instanceof Error ? e.message : "Unknown error",
            "INTERNAL_ERROR",
          );
        }
      },
    );
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that the tool 'Creates a decision record and cross-posts to the blackboard', which implies a write operation, but doesn't address permissions, side effects, error handling, or what 'traceability' entails in practice. For a complex 15-parameter mutation tool, this leaves significant behavioral gaps.

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 concise sentences that efficiently convey the core functionality and secondary action. Every word earns its place—no fluff or redundancy.

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

Completeness2/5

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

For a complex mutation tool with 15 parameters, no annotations, and no output schema, the description is insufficient. It lacks details on behavioral traits (e.g., idempotency, side effects), expected return values, or error conditions. The mention of 'traceability' is vague without elaboration.

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 schema description coverage is 100%, so all parameters are documented in the schema. The description adds no additional parameter semantics beyond what's in the schema (e.g., it doesn't explain how 'cross-posts to the blackboard' relates to parameters). Baseline 3 is appropriate when the schema does the heavy lifting.

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's purpose with specific verbs ('Record a decision', 'Creates a decision record and cross-posts') and resources ('decision record', 'blackboard'). It distinguishes from siblings like twining_search_decisions (which searches) or twining_post (which posts without the full decision structure).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to choose twining_decide over twining_post (for simpler posts) or twining_search_decisions (for retrieval), nor does it specify prerequisites or exclusions for decision recording.

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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