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yinnho

AginxBrowser

session_export

Read-only

Export a recorded browser session's action log as a runnable curl script to replay all actions in a new session, or as JSONL for automation and analysis.

Instructions

Export a browser session's recorded action log. Format "bash" (default) returns a runnable curl script that replays every recorded action (navigate/click/input/scroll/eval) against a fresh session on this server — hand it to a shell or cron, zero model tokens. Format "jsonl" returns the raw action log, one JSON object per line.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
formatNoOutput format: "bash" (default) renders a runnable curl script that replays every recorded action against a fresh session; "jsonl" returns the raw action log, one JSON object per line
session_idYesSession ID

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations mark this as readOnlyHint=true, and the description aligns with that by describing an export operation. It adds valuable behavioral detail beyond the schema: the bash output replays actions against a fresh session, is meant to be handed to a shell or cron, and consumes zero model tokens. No side effects or destructive actions are implied.

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 carefully structured sentences: the first states the core function, the second explains both format options and their use cases. Every clause earns its place, and the most important decision (which format) is presented immediately after the purpose.

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?

For a simple two-parameter export tool with read-only annotations and no output schema, this description is complete. It covers both possible formats, their outputs, and a concrete use case. An agent knows exactly what to expect from the tool and can invoke it correctly with just session_id.

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?

Schema description coverage is 100%, so the baseline is 3. The description adds a little extra context (e.g., 'navigate/click/input/scroll/eval' and 'zero model tokens'), but the core parameter meanings are already fully documented in the schema. The added value does not push it above 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 leads with a specific verb and resource: 'Export a browser session's recorded action log.' It then differentiates the two output formats (bash replay script vs. jsonl raw log), which clearly separates it from sibling session tools like session_list or session_state. Purpose is unambiguous.

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?

The description gives clear usage context: format 'bash' is explicitly tied to creating a runnable curl script for shell/cron with zero model tokens, and format 'jsonl' is tied to getting the raw per-line log. It doesn't explicitly name sibling alternatives or exclusions, but the use cases are concrete and imply when this tool is appropriate.

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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