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nightly_run

Processes unsettled deals across all companies in a batch pipeline, classifying each by confidence level and routing for automatic posting or human review.

Instructions

Nightly batch pipeline. Processes ALL companies accessible by the token (= multi-company batch). Pipeline per company: fetch unprocessed (status=unsettled) → Stage 0 exclusion → Stage 1+2 classify → confidence routing (high=auto, medium=auto+log, low=human_review) → aggregate summary. Currently dry-run only (write-back pending Phase 1.B).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dry_runNoCurrently always dry_run (= write-back pending Phase 1.B)
period_endNoYYYY-MM-DD end date filter
company_idsNoOverride: process only these company IDs (default: all accessible)
concurrencyNoMax parallel companies (default: 3, freee rate limit safe)
period_startNoYYYY-MM-DD start date filter
deals_per_companyNoMax deals fetched per company
Behavior5/5

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

With no annotations provided, the description fully carries the burden of disclosing behavior. It reveals the tool is currently dry-run only, processes all companies, and details the per-company pipeline steps (fetch, exclusion, classification, confidence routing, summary). This is transparent about limitations and internal logic.

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 and front-loaded with the tool's purpose. It uses a single paragraph with key points (pipeline steps, dry-run status) without unnecessary words. Every sentence adds value.

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 (batch pipeline with multiple stages, no output schema), the description provides a good overview of the process and current state. It covers the pipeline steps and dry-run limitation. However, it lacks details on what the tool returns or how to interpret results, which could be useful for an agent.

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 all parameters are already described in the input schema. The tool description adds minimal extra information (e.g., dry-run context) but does not significantly enhance understanding beyond the schema's parameter descriptions. Baseline score of 3 is appropriate.

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 is a nightly batch pipeline that processes all accessible companies. It outlines the pipeline stages (fetch, exclusion, classify, routing, summary), distinguishing it from sibling tools that handle individual operations like classify_transaction or check_duplicate.

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 explains the tool is for batch processing and notes the current dry-run limitation. It implies when to use (nightly runs) but does not explicitly exclude alternatives or provide when-not-to-use guidance. However, the pipeline context is clear.

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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