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delimit_ledger_propose

Analyzes repository state, signals, and completed work to propose 3-5 new ledger items with rationale, maintaining momentum at the end of build loops or when the queue is empty.

Instructions

Propose new ledger items based on signals, completed work, and gaps.

Analyzes repo state, sensing signals, and completed work to suggest 3-5 new items with rationale. Run at end of build loops or when the queue is empty to keep momentum.

Works across all AI models via MCP.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ventureNoFocus on a specific venture (auto-detects if empty).
focusNoOptional area filter - "outreach", "engineering", "security", etc.
max_itemsNoMaximum proposals to generate (default 5).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

With no annotations, the description must disclose behavior fully. It mentions analyzing repo state and signals to generate proposals, but does not detail side effects, permissions, or data handling. This is adequate for a non-destructive generative tool but could be more thorough.

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 concise, with a clear lead sentence followed by two explanatory sentences. Every sentence provides essential information without redundancy, making it efficient for an agent to parse.

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?

Given the tool's complexity (proposing items based on signals) and the presence of an output schema, the description adequately covers inputs, outputs, and usage context. It explains why and when to use it, making it complete for an agent.

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 each parameter documented. The description adds value by noting that `venture` auto-detects when empty, which is not in the schema. This enhances understanding beyond the schema.

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 proposes new ledger items based on signals, completed work, and gaps, specifying it analyzes repo state and suggests 3-5 items with rationale. This distinguishes it from sibling tools like `delimit_ledger_add` and `delimit_ledger_list`.

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 explicitly advises using this tool at the end of build loops or when the queue is empty to maintain momentum. While it does not list alternatives or when not to use, it provides clear context for optimal invocation.

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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