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get_experiment_timeline

Generate a chronological timeline of experiments from Markdown notes, extracting changes, outcomes, and decisions for comparison and reproducibility.

Instructions

扫描指定目录下的 Markdown 实验笔记,提取改动、好坏评定与采纳决策,生成按时间排序的实验时间线.

参数: notes_dir: 存放实验笔记的目录路径。若不提供,优先读取环境变量 LABLOG_NOTES_DIR 或当前工作目录。 limit: 最多返回的实验条目数,默认 20。 topic: 可选的关键词过滤(如 'LoRA', 'prompt', 'temperature')。 order: 时间排序方式,'desc' (最新实验优先) 或 'asc' (最早实验优先)。

Input Schema

NameRequiredDescriptionDefault
limitNo
orderNodesc
topicNo
notes_dirNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It does disclose genuine behavior beyond the schema: the notes_dir resolution fallback (env var LABLOG_NOTES_DIR, then cwd) and the default/output-limiting behavior. However it never states the read-only nature explicitly, nor what happens when the directory is missing or unreadable. Adequate but incomplete.

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 front-loaded with a one-sentence purpose followed by a tight parameter list, with no filler or repetition. It is appropriately sized for a four-parameter tool, though the parameter block could be slightly tighter.

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?

An output schema exists, so return values need not be described, and all four parameters are documented in the description. The remaining gap is the absence of guidance on when to use this versus the sibling detail tool, which leaves the selection decision under-supported.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must supply all parameter meaning, and it does: it explains notes_dir's fallback chain, limit's default of 20, topic's filter semantics with examples ('LoRA', 'prompt'), and supplies the 'desc'/'asc' enum values that the schema itself omits. Only minor formatting/path details are left out.

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 gives a specific verb chain and resource: it scans Markdown experiment notes in a directory, extracts changes/ratings/decisions, and produces a time-ordered timeline. That is far more concrete than the tool name alone. It stops short of differentiating itself from the sibling get_experiment_detail, so it doesn't reach a 5.

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 guidance and no mention of the sibling get_experiment_detail, which is the obvious alternative for drill-down. The only contextual hints (sort order, topic filtering) are parameter semantics, not usage framing. An agent must infer when this tool is preferable.

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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