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by ExQA

get_recording_snapshot

Load a saved Charles recording (.chlsj) to inspect historical traffic. Use this when you need data from a past session, not live Charles data.

Instructions

Load a saved recording snapshot. This tool never reads the live Charles session. HISTORY-PLANE TOOL — only use when the user explicitly references a saved recording (.chlsj file).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathNo
itemsYes
sourceYes
warningsNo
total_itemsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations provided, the description carries the full behavioral burden. It discloses that the tool does not read the live capture and is a history-plane tool, but it does not explicitly state whether loading is side-effect-free, read-only, or whether internal state is modified. More detail on side effects or read-after-load behavior would be needed for full transparency.

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 three sentences long and every sentence adds value: the primary action, the distinction from live session, and the trigger for use. It is front-loaded with the core action and uses plain, unambiguous language with minimal fluff.

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

Completeness3/5

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

The tool is simple, has an output schema, and the description provides strong guidance on when and how to use the tool, plus a useful negative (no live access). However, the path parameter remains undocumented, and the default/required behavior is not explained. Given the lack of annotations, this minor gap keeps it from being fully complete for an AI agent.

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 0%, so the description must compensate; it mentions save as .chlsj files but never directly maps the path parameter to a file path or explains its meaning. The schema only offers a nullable, foreign path with a default of null. An agent is left guessing whether path is required, what format it should take, or how the default is resolved.

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 loads a saved recording snapshot and explicitly distinguishes it from live-session tools by asserting it never reads the live Charles session. It also specifies the file type (.chlsj), which helps an agent identify both the resource and the input type. This is specific and separates it from sibling live-capture and recording-analysis tools.

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 explicit when-to-use guidance: only when the user references a saved recording (.chlsj file). It also clearly states a when-not condition: 'never reads the live Charles session'. While it does not name a specific alternative tool (e.g., read_live_capture), the contextual boundary is strong enough for an agent to select or avoid it.

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