Skills Development Elephant Resolution Skill

Elephant Resolution Skill

v20261103
egm-resolve
Processes deficiency reports from Goldfish reviewers, categorizes findings into contest/escalate/propose fix/decline categories, generates audit reports, and manages interactive resolution gates for code review workflows with automated fixes and human-in-the-loop approval
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Overview

Goldfish Review: Resolve

When running in Codex or ChatGPT Work, first read Codex integration.
In Claude Code or Cowork, read ${CLAUDE_PLUGIN_ROOT}/docs/claude.md first.

Overview

This skill instructs the agent on how to operate within the primary Elephant
context window to parse flat deficiency reports from concurrent Goldfish
reviewers. It defends accurate design choices, applies automated textual
repairs, and manages interactive negotiation checkpoints.

Prerequisites & Context Strategy

  • Context Recommendation (Elephant Memory): This skill should be run in

the persistent conversation session that generated the target document (the
Elephant) to recall earlier reasoning and craft higher-quality fixes.

Inputs

The caller or orchestration driver provides exactly these parameters:

  • TargetFile: Absolute or relative path to target document.
  • LineRange: Exact line numbers (or full file).
  • FindingsList: Aggregated flat list of findings from Goldfish

reviewers.

Execution Workflow

Step 1: Intake Validation & Gather Context

  1. Hybrid Execution UX: Detect if execution arguments are present:
  • Automated Mode: If all parameters are provided, execute silently as a

subprocess.

  • Standalone Human Mode: If parameters are omitted, trigger a friendly

onboarding flow. Prompt for one piece of input at a time, waiting for
the user's response after each turn. Once all inputs are specified,
display the final setup and verify the user is ready to continue.

  1. Read TargetFile at LineRange by reading it and parse the FindingsList.

Step 2: Evaluate & Categorize

Give each finding exactly one category:

  • CONTEST: The critique is inaccurate or relies on a misunderstanding of

the codebase. Cite evidence that the reviewer could read: a file and
symbol, or a decision recorded in the document.

  • ESCALATE: The critique is inaccurate, but the evidence is outside every

file the reviewer could read (for example, a team convention or a verbal
decision). State that fact. Do not fix the finding. Give it to the user.

  • PROPOSE FIX: The critique is valid. Define precise textual replacements

or structural formatting adjustments to resolve the gap.

  • DECLINE: The finding is a Nit. Record it. Do not fix it. You can use

PROPOSE FIX for a Nit if the fix is worth it.

Apply these rules:

  • A contest must be checkable. "This was intentional" is not evidence.

If you cannot cite evidence the reviewer could read, use ESCALATE or
PROPOSE FIX.

  • Do not add context only to satisfy a reviewer. Add context when a human

reader of the document needs it. If only a zero-context subagent needs it,
use ESCALATE.

  • Do not contest a comprehension gap. If a fresh reader could not follow

the document, the document is missing context.

  • Do not change a severity. If you think a Blocker is a Nit, CONTEST it

and state the reason.

  • You wrote the document under review. A wish to contest is not evidence

that the reviewer is wrong.

Step 3: Report Fixes

Construct the final report and save it named
goldfish_review_report.md in the working directory (or your harness's artifact directory, if it has one)
using your file-writing tool. Use this layout:

# Goldfish Annotated Review Report

**Target:** `[TargetFile]` (`[LineRange]`)

## Prioritized Findings & AI Suggestions

{{range findings, ordered by Severity}}
### [Issue 1] [`[ReviewerPersona]`] - Severity: [Blocker | Major | Nit]
*   **Affected Scope:** [Lines Start-End]([RelativePath]#L[Start]-L[End]) ([Sub-header])
*   **Discrepancy Description:** [copied from FindingsList]
*   **Rationale:** [copied from FindingsList]
*   ***AI Suggestion:*** [CONTEST | ESCALATE | PROPOSE FIX | DECLINE]
*   ***Justification:*** [Detailed reason]
*   ***Proposed Edit:***
    *   Location: [Line/Header]
    *   Change: [Precise replacement string or deletion note]
{{end}}

Step 4: Interactive Resolution Gate

If any finding is ESCALATE, list those findings first in the chat message.
They need the user's knowledge, not only approval.

Before proceeding, output a visible chat message to the user: *"I have compiled
the audit findings into goldfish_review_report.md. Please review the findings there and choose how you would like to
proceed:

  • Comment directly on the file: Review goldfish_review_report.md in

chat or the file and leave comments/edits to approve, reject, or contest
specific items.

  • Auto accept: Reply "auto accept" to batch-apply all proposed fixes

(skipping contested items).

  • Continue to next phase: Reply "continue" or "no changes" to proceed

without applying fixes.

  • Interactive breakdown: Reply "interactive breakdown" for a guided,

item-by-item walkthrough in chat with detailed explanations for each
proposed edit or contested finding before making decisions.

  • Custom instruction / Wildcard request: Reply with any custom

instruction, question, or out-of-band request."*

You MUST immediately yield active execution by calling zero tools in
this turn payload. You must stop execution and go idle, waiting for the human
developer to comment on/edit the artifact or reply in the chat.

Interpret the user's action/response as follows:

  • **"Auto accept" / "Accept all suggestions" / User clicks "Proceed" without

contesting**: Apply all fixes where the AI suggestion was PROPOSE FIX
directly to TargetFile at LineRange in a single batch using
your file-editing tool. Any items categorized as CONTEST, ESCALATE, or
DECLINE are explicitly bypassed. Then proceed to Step 5.

  • "Continue to next phase" / "No changes": Do not apply any automated

fixes. Then proceed to Step 5.

  • "Interactive breakdown": Enter a sequential breakdown loop over ALL

finding items (all categories except DECLINE):

  1. For each item i, output a visible chat message formatting the full

finding details and explanation in rich markdown:

```markdown

Breakdown Item [i]: [Issue Title] [[ReviewerPersona]]

  • Scope: Lines Start-End ([Sub-header])
  • Description: [Description]
  • AI Suggestion: [CONTEST | ESCALATE | PROPOSE FIX]
  • Explanation & Justification: [Detailed reason and background explaining why the fix is proposed or why the finding is contested]
  • Proposed Edit: [Precise replacement text or deletion note]

```

Then prompt the user in chat for their decision on this item (calling
zero tools and going idle):

  • If PROPOSE FIX: Ask the user to reply with **Accept proposed

fix, Skip / ignore, or Discuss**.

  • If CONTEST: Ask the user to reply with **Skip / agree with

contest, Overrule contest (propose fix), or Discuss**.

  • If ESCALATE: Ask the user to reply with Confirm (no change),

Add the fact to the document, or Discuss.

  1. Record the user's decisions in an internal memory checklist (e.g., *Item

1: Accepted, Item 2: Ignored, Item 3: Overruled*). **Do NOT call any
file editing tools during this sequential loop.**

  1. Once all items have been decided, summarize the accepted edits, execute

them using your file-editing tool, and proceed to Step 5.

  • Custom instruction / Out-of-band edit: If the user provides targeted

instructions, apply them and proceed.

Step 5: Post-Resolution Synchronization & Exit

  1. Re-verify Lines: If changes were made to TargetFile, verify that the

file remains structurally coherent and valid markdown.

  1. Mark the report as resolved (add a Status: resolved line at the top).
  2. Handoff: Exit cleanly back to the caller (such as egm-review-loop)

with the count of accepted fixes, contested items, escalated items,
declined items, and remaining unaddressed issues.

Info
Category Development
Name egm-resolve
Version v20261103
Size 4.32KB
Updated At 2026-11-04
Language