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debug_why_transcript_failed

Identify why a transcript failed by correlating failure symptoms with ABL file/line diagnoses. Analyze transcript JSON and package files to pinpoint root causes.

Instructions

[Arch Optimize] Arch validates packages, inspects compiler-visible models, and drives repair loops. Given a transcript JSON and exported package folder/.zip or file map, correlate transcript failure symptoms with ABL file/line diagnoses such as finalize -> COMPLETE -> RESPOND: "".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNoOptional import-style payload. data.files is accepted as the package file map.
pathNoLocal project folder or .zip path to inspect
filesNoRelative path -> UTF-8 file content map
transcriptNoTranscript JSON object or JSON string
transcriptPathNoLocal path to a transcript JSON file

Schema Changelog

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

  1. First observedv1.5.0

TDQS

C2.7/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions 'drives repair loops' but this seems to refer to the broader Arch system, not necessarily this tool. It does not disclose whether the operation is read-only or has side effects, nor what the tool actually returns. The example diagnosis format is fragmentary and ends with an unmatched quote.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a long, run-on sentence that mixes a system-level preamble with a tool-specific explanation. The '[Arch Optimize]' tag and first clause are tangential and could be trimmed. The ending is malformed with a stray colon and quote, suggesting truncation. The core function is buried in the second half.

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

Completeness2/5

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

With five parameters, multiple input alternatives, and no output schema, the description should explain what the tool returns and its behavioral promise. It fails to mention the output format or any side effects. The example diagnosis is cryptic and incomplete. An agent would be left uncertain about the result and side effects.

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 schema already documents all five parameters. The description adds minor value by clarifying that the package can be supplied as a path or files map and the transcript as an object or path, but this is largely inferable from the schema. No additional semantic depth is provided.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description eventually states a specific verb+resource: 'correlate transcript failure symptoms with ABL file/line diagnoses'. This is concrete enough to infer the tool's core function. However, it opens with a confusing preamble about 'Arch validates packages...' that does not directly describe this tool and could mislead. It does not explicitly differentiate from siblings like debug_diagnose_transcript.

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

Usage Guidelines2/5

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

No explicit when-to-use or when-not-to-use guidance is given. It lists input preconditions ('Given a transcript JSON and exported package...') but does not contextualize this against alternatives. An agent would have to guess when to call this over debug_diagnose_transcript or debug_diagnose.

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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