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Cassette-Editor

oh-my-cassette

cassette_edit

Perform surgical timeline edits—trim, text, delete, undo—using the manual editor lane after reading the timeline. Include expected_version to confirm the current state.

Instructions

Surgical no-LLM timeline edit through the manual-editor command lane (requires CASSETTE_DIRECT_EDIT=1). Use for small named changes (trim, text, delete, undo) after reading cassette_timeline; big or creative briefs go through cassette_run_job. input is always {"payload": {...}}. Pass expected_version from the last timeline read; tool_name 'undo' with input.cursorSequence rewinds the shared operation history.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputNo
tool_nameYes
session_idYes
expected_versionNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYes
dataNo
errorNo
phaseYes
job_idNo
warningsNo
artifactsNo
session_idNo
next_actionYes

Schema Changelog

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

  1. Changed1 schema field changedv0.4.19
    • addedOutput schema / $defs / Artifact / properties / expires_at
      Added value: +{
      +  "anyOf": [
      +    {
      +      "type": "string"
      +    },
      +    {
      +      "type": "null"
      +    }
      +  ],
      +  "default": null,
      +  "title": "Expires At"
      +}
  2. Addedv0.4.6
  3. Removedv0.1.1
  4. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral disclosure burden. It reveals that the tool is a direct, no-LLM command-lane edit, requires a specific environment flag, expects a specific input envelope, relies on expected_version, and describes how undo rewinds shared history. This is strong disclosure, though it does not detail all side effects or failure conditions.

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?

Three dense sentences deliver purpose, usage boundaries, prerequisites, input shape, versioning, and undo behavior without repetition. The most important trait ('Surgical no-LLM timeline edit') is front-loaded, and every clause adds signal.

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?

Given the output schema exists and the tool is moderately complex, the description covers the critical call pattern, prerequisite, workflow order, and differentiation from cassette_run_job. The main remaining gap is undocumented session_id semantics and the full set of tool_name values, but an agent can still invoke the tool correctly with what is provided.

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 0%, so the description must compensate. It usefully explains that input is always a payload wrapper, that expected_version comes from the last timeline read, and that tool_name 'undo' pairs with input.cursorSequence. However, it does not explain session_id semantics or enumerate the other valid tool_name values, leaving part of the parameter surface undocumented.

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 states a specific verb and resource: 'Surgical no-LLM timeline edit through the manual-editor command lane.' It names concrete operations (trim, text, delete, undo) and explicitly contrasts itself with cassette_run_job. An agent can immediately tell what this tool does and how it differs from siblings.

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?

The description gives explicit when-to-use guidance: 'Use for small named changes... after reading cassette_timeline' and 'big or creative briefs go through cassette_run_job.' It also flags the required environmental prerequisite CASSETTE_DIRECT_EDIT=1, leaving little ambiguity about when this tool should be selected.

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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