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get_decisions

Retrieves all confirmed technical decisions for a project with cited sources and jump-back links, helping AI coding agents recall prior choices and resolve context gaps.

Instructions

本项目全部已确认技术决策(带出处,可回跳)

Input Schema

NameRequiredDescriptionDefault
topicNo
sourceNo
projectNo项目根绝对路径。仅当服务端提示 unresolved_project(多项目/未自动识别)时选择传此参;传一次后本连接记住

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.0

TDQS

C2.9/5.0
Behavior3/5

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

There are no annotations, so the description carries the full burden. It correctly signals read-only enumerative semantics and adds genuinely useful result context (each decision has provenance and can be jumped back to). It omits scope/auth behavior, pagination, ordering, and what happens when the project is unresolved — which matters since the project parameter exists precisely for that failure mode.

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?

A single compact clause, front-loaded with scope ('本项目') before the qualifier about provenance. Zero waste, but it is arguably under-specified rather than concise — the terseness comes at the cost of the missing parameter and usage information.

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

Completeness2/5

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

For a 3-parameter tool with no annotations and no output schema, the description is too thin. An agent still does not know what topic/source filter on, whether results are paginated or ordered, or how this differs from session-level lookup tools. Only the provenance/backlink hint partially fills the gap left by the absent output schema.

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 33%: only the project parameter is documented, and quite well. The description's phrase '本项目' loosely implies project scoping but says nothing about the topic and source parameters, and does not explain how they interact or whether they narrow the 'all' list. With low coverage the description should have compensated, and it does not.

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

Purpose4/5

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

The description names the specific resource: all confirmed technical decisions for '本项目' (the current project), and adds that each carries provenance and a backlink. That is more than a restatement of the name. It does not, however, contrast itself with siblings like search_sessions or get_session_detail, which an agent might otherwise reach for when looking for decisions.

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

Usage Guidelines2/5

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

There is no explicit when-to-use or when-not-to-use guidance, and no alternatives are named. The word '全部' (all) hints that this is an unfiltered enumeration, but the presence of topic and source parameters suggests filtering is possible, and the description never resolves that ambiguity.

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