ledger_log_approach

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

Beyond the annotations, the description discloses return format ('dict: {"id": int}'), error behavior (ValueError with message naming valid values), and the critical stable-task-identifier requirement. It also enumerates outcome values with meanings. This provides significant operational context beyond the sparse annotation flags.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is organized with a strong opening sentence, then a practical usage note, and a well-formatted Args section. Each sentence provides necessary guidance with no filler. It is appropriately sized for a tool with four parameters and meaningful behavioral constraints.

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

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

The description covers when to use, what the parameters mean, what the return value is, and potential errors. The output schema already documents return structure, so the description need not repeat it. Sibling tools are mentioned via ledger_check_approaches, providing integration context. This is a complete, self-contained description.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description fully compensates. It explains task as a stable identifier to reuse across approaches, approach as a short non-empty description, outcome with the allowed enum and their implications, and reason as a required explanation. This is far more informative than the bare schema properties.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with 'Record the outcome of an approach tried (or considered) for a task.' This clearly specifies the verb (record), resource (approach outcomes), and scope (per task). It also distinguishes itself from siblings by referencing ledger_check_approaches as a companion and focusing specifically on approaches rather than actions or dispatches.

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

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

The description gives explicit when-to-use guidance: 'Record every failed approach IMMEDIATELY after it fails, and every deliberate NO-GO decision.' It explains the purpose (avoid re-discovering dead ends). However, it does not explicitly state when not to use this tool or name alternatives such as ledger_log_action, so it lacks formal exclusions but provides clear context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.