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dl4rce

flaiwheel

by dl4rce
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

save_session_summary

Record session accomplishments, decisions, and next steps to a project log for continuous context across coding sessions.

Instructions

Append a session summary to the project's session log.

    Side effects: appends a JSON entry to /data/sessions-{project}.json.
    Does not modify the vector index or the knowledge repo. Safe to call
    multiple times in one session — each call adds a new entry.

    Call at the END of every session. Use get_recent_sessions() at the
    START of the next session to restore context.

    Args:
        summary: What was accomplished this session (1–3 sentences)
        decisions: Key decisions made, comma-separated (optional)
        open_questions: Unresolved questions or next steps, comma-separated (optional)
        files_modified: Files changed, comma-separated (optional)
        project: Target project name (optional)

    Returns:
        Confirmation with the project name and total session count stored.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectNo
summaryYes
decisionsNo
files_modifiedNo
open_questionsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Tool Definition Quality

A5/5.0
Behavior5/5

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

Discloses side effects (appends to JSON file, does not modify vector index or knowledge repo), states it is safe to call multiple times, and explains each call adds a new entry. No annotations were provided, so the description fully carries the burden.

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?

Well-structured with clear sections: main purpose, side effects, usage, arguments, returns. Every sentence adds value, and the information is front-loaded. Despite length, it is appropriately concise for the detail needed.

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

Completeness5/5

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

Covers all necessary aspects: what the tool does, side effects, when to use, parameter details, and return value. With no annotations and a low schema coverage, the description provides complete context for correct agent usage.

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 includes an Args section that explains each parameter's purpose (e.g., summary: 1–3 sentences, decisions: comma-separated, optional). The schema only has types and defaults, so the description adds significant meaning.

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 appends a session summary to the project's session log, using a specific verb and resource. It distinguishes itself from sibling tools like get_recent_sessions by explaining the complementary usage.

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

Usage Guidelines5/5

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

Explicitly instructs to call at the END of every session and to use get_recent_sessions at the start of the next session, providing clear when-to-use guidance with an alternative tool.

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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