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Update a project decision or learning

update_project_decision

Revise a recorded decision, learning, preference or constraint on a project when the thinking changes. Editing keeps one authoritative record instead of contradictory duplicates future teammates must reconcile.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNo
detailNo
summaryNo
task_idNo
decision_idYes

TDQS

A4/5.0
Behavior4/5

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

The annotations already signal a non-read-only, non-destructive write operation. The description adds meaningful context beyond that: this tool updates in place to preserve 'one authoritative record' and avoid contradictory duplicates. It does not cover permissions or side effects, but the core behavioral rationale is clear.

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?

Two tight sentences. The verb and resource appear immediately, and the second sentence justifies the tool's existence without repeating the title or annotations.

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

Completeness3/5

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

Given the simple update operation and the provided schema types, the description is adequate for orienting an agent. Still, with no output schema and no property descriptions, it leaves gaps around how to use `task_id` and which fields are actually updated, so it is not fully complete.

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

Parameters2/5

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

Schema description coverage is 0%, so the description carries the full burden for explaining parameters, but it never mentions `decision_id`, `summary`, `detail`, or `task_id`. It only echoes the `kind` enum values already present in the schema. An agent receives no guidance on which fields to supply when revising a decision.

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?

States a specific verb ('Revise') and resource ('recorded decision, learning, preference or constraint on a project'), and distinguishes the tool from logging/creating by emphasizing editing an existing record. The four categories also map cleanly to the `kind` enum, so an agent knows exactly what the tool operates on.

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?

Gives a clear trigger condition: 'when the thinking changes.' It also implicitly tells agents not to create contradictory duplicates. However, it does not explicitly name the alternative tool (e.g., log_project_decision) for recording a brand-new decision, so the exclusion is implied rather than explicit.

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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TDQS

A3.7/5.0
Disambiguation3/5

Most tools target a distinct resource and action, but several adjacent pairs are easy to confuse: add_comment vs add_progress_note, call_executor vs call_integration, log_client_decision vs update_client_context vs memory_save, and list_context_sources vs list_integrations. The descriptions do disambiguate them, but the boundaries are subtle enough that misselection is likely with 81 tools.

Naming Consistency4/5

The overwhelming majority follow a clear verb_noun snake_case pattern (create_task, update_project, list_integrations, set_webhook), and get_/ list_/ create_/ update_ families are predictable. Minor deviations exist: memory_read/memory_save/memory_search invert to object_verb, and bare nouns like whoami, glossary, and security_posture break the pattern, but there is no chaotic casing or mixed conventions.

Tool Count2/5

At 81 tools, this is far above the weight that is comfortable for an agent's tool-selection surface, especially since many tools belong to families that could be consolidated (webhooks, worker keys, project logs, context/memory). Although the domain is broad, the count will overwhelm agents and increase misrouting.

Completeness4/5

The surface is unusually comprehensive: tasks, projects, workers, leases, artifacts, comments, handoffs, webhooks, keys, context, memory, integrations, and support all have create/read/update/delete or equivalent lifecycle coverage. The gaps are minor, such as remove_dependency without a visible add_dependency and no artifact/comment deletion, but agents can work around them.

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