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download_log

Fetch and summarize compilation logs from Typleaf projects. Parses Typst errors and warnings into a compact list; returns raw LaTeX logs.

Instructions

Fetch the compilation log from Typleaf and summarise it. For a Typst project the log holds typst's own error: / warning: diagnostics with file:line:column (typst writes no TeX-style log at all), and this tool parses them into a compact list. For a LaTeX project the raw log is returned. Requires TYPLEAF_SESSION.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rawNoReturn the unparsed log text even for a Typst project. Default false.
project_idYesTypleaf project ID — a 24-character lowercase hex string (e.g. '692a83fb82feceb233c4b0e7'), obtained from list_projects or the project URL. NOT a local filesystem path, NOT '.', NOT a project name or title. These tools operate on the REMOTE Typleaf project. Only call these tools when the user explicitly asks to work with a Typleaf project — never for general local file I/O. If you already have a copy of THIS project checked out on the local filesystem, prefer the standard read/grep tools against that path. Always call list_projects first when unsure.
Behavior4/5

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

The description reveals key behaviors beyond annotations: it parses Typst logs into a compact list, returns raw logs for LaTeX, and requires TYPLEAF_SESSION. Annotations only say readOnlyHint=false, idempotent=false, destructive=false, which are not contradicted but also not informative. The added behavioral detail is valuable.

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?

The description is a single dense sentence with zero fluff. It front-loads the action, then explains the Typst/LaTeX difference, and ends with the session requirement. Every word earns its place.

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?

It covers the core action, the two project-type behaviors, and a prerequisite. With no output schema, the description does indicate return format (compact list vs raw). It lacks mention of failure modes or session expiration, but for a 2-parameter read-like tool, it is sufficiently complete.

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

Parameters3/5

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

The schema descriptions cover both parameters (raw and project_id) exhaustively, including the default and format. The tool description adds no parameter-specific guidance beyond contextual behavior (e.g., raw for LaTeX), so it does not elevate beyond the schema baseline.

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 uses a specific verb ('Fetch') and a clearly defined resource ('compilation log from Typleaf'). It also distinguishes between Typst and LaTeX behaviors, which immediately separates it from sibling tools like download_pdf or download_source. The purpose is unmistakable.

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?

It clearly states the tool is for compilation logs and gives context for both project types, which tells an agent when to reach for it. However, it does not explicitly name alternatives or say 'use X instead', but the resource is distinct enough that an agent can infer when to use it.

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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