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project_status_report

Identifies at-risk and off-track projects by analyzing milestones and end dates, ranks by risk, and flags health divergence.

Instructions

Report which projects are in trouble, across a portfolio, in one call.

Composes project.project records (filtered by manager / customer / name) with their project.milestone rows into a per-project derived health verdict (off_track / at_risk / on_track) driven by overdue-or-unreached milestones and the project end date. Surfaces the PM's declared status alongside, flags projects declared healthier than the data (divergence), and ranks by risk.

Args: manager: Optional project-manager filter (user_id.name ilike). customer: Optional customer filter (partner_id.name ilike). project: Optional project-name filter (name ilike) to narrow the set. include_on_hold: Keep projects whose declared status is on_hold (default True). include_done: Keep projects whose declared status is done (default False). lookahead_days: Days ahead that count as "due soon" for at_risk (default 7). timezone_offset: UTC offset for "today" (default 7 = Asia/Ho_Chi_Minh).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
managerNo
projectNo
customerNo
include_doneNo
lookahead_daysNo
include_on_holdNo
timezone_offsetNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries full burden and explains the derivation process (milestones, health verdict, divergence flag, risk ranking). It does not disclose auth needs or rate limits but sufficiently details the computational behavior.

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

Conciseness4/5

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

The description is well-structured with a clear summary followed by details and parameter list. It is slightly verbose but each sentence adds value; minor improvements could tighten phrasing.

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 (7 params, derived health logic) and presence of an output schema, the description covers core behavior comprehensively. It does not mention pagination or ordering but is otherwise complete.

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

Parameters5/5

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

The description adds substantial meaning beyond the schema for all 7 parameters, including filtering semantics (ilike), default values, and purpose. Despite 0% schema description coverage, the description fully compensates.

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 reports which projects are in trouble across a portfolio, deriving health verdicts. This is specific and distinct from sibling tools like business_pulse or inventory_risk, which cover different domains.

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

Usage Guidelines3/5

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

The description provides parameter filters but does not explicitly guide when to use this tool versus alternatives like 'pipeline_review' or 'sprint_health'. No 'when not to use' or comparison is given, leaving some ambiguity for the agent.

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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