From agent-validator
Files structured GitHub bug reports for agent-validator by collecting runtime evidence (config, debug logs, execution state) and drafting issues. Useful when users encounter a suspected defect.
How this skill is triggered — by the user, by Claude, or both
Slash command
/agent-validator:validator-issueThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
Collect runtime evidence, draft a structured GitHub issue for a suspected agent-validator bug, present a full preview, and file only after confirmation — unless invoked in auto-file mode.
Collect runtime evidence, draft a structured GitHub issue for a suspected agent-validator bug, present a full preview, and file only after confirmation — unless invoked in auto-file mode.
Check for auto-file mode: If $ARGUMENTS begins with --auto-file , set auto-file mode to on and strip the prefix to get the remaining text as the bug description. Skip the confirmation step (Step 4) when auto-file mode is on.
Get the description:
If a non-empty description remains after stripping any --auto-file prefix, use it as the bug description and proceed to Step 2.
If $ARGUMENTS is empty (or becomes empty after stripping), ask the user:
"Please describe the bug you encountered with agent-validator. What happened, what did you expect, and what were you trying to do?"
Wait for their response before continuing.
Read .validator/config.yml first to resolve log_dir (default: validator_logs if the field is absent or the file doesn't exist).
Collect the following evidence. For each item, note if it is absent — do not fail if files are missing:
.validator/config.yml in full.<log_dir>/.debug.log.
tail -n 50 <log_dir>/.debug.log
<log_dir>/.execution_state.Record which files were found and which were absent.
Draft a GitHub issue with the following structure:
## Problem
<A clear, concise description of the bug. Based on the user's description.>
## Steps to Reproduce
<Step-by-step instructions to reproduce the issue. Infer from the description and evidence, or note "Not yet determined" if unclear.>
## Expected vs Actual
**Expected:** <What should have happened>
**Actual:** <What actually happened>
## Evidence
> **Before including evidence, redact sensitive values**: remove or replace tokens, API keys, email addresses, and absolute local paths that may appear in config, logs, or state. Replace them with `[REDACTED]` or a generic placeholder.
**Config (`.validator/config.yml`):**
<Paste only relevant, non-sensitive config values. Redact tokens, emails, and absolute paths. Note "File not found" if absent.>
**Debug log (last 50 lines of `<log_dir>/.debug.log`):**
<Paste minimal relevant excerpt with sensitive values redacted. Note "File not found" if absent.>
**Execution state (`<log_dir>/.execution_state`):**
<Paste only fields needed to diagnose the bug; redact sensitive values. Note "File not found" if absent.>
**Absent files:** <List any files that were not found, or "None">
Choose a concise, descriptive title: Bug: <short summary of the problem>.
Present the full draft to the user — both title and body.
If auto-file mode is on: Inform the user that the issue will be filed automatically (show the title and body), then proceed directly to Step 5 without asking.
Otherwise, ask:
"Here is the draft issue. Shall I file it? (yes/no)"
Write the issue body to a temporary file and pass it via --body-file to avoid shell interpolation issues with special characters in the body text:
ISSUE_TITLE=$(cat <<'TITLE_EOF'
Bug: <short summary>
TITLE_EOF
)
BODY_FILE=$(mktemp)
cat > "$BODY_FILE" << 'ISSUE_EOF'
<paste the full issue body here>
ISSUE_EOF
gh issue create --repo Codagent-AI/agent-validator --title "$ISSUE_TITLE" --body-file "$BODY_FILE"
rm -f "$BODY_FILE"
Report the created issue URL to the user.
npx claudepluginhub codagent-ai/agent-validator --plugin agent-validatorCreates GitHub issues in WaterplanAI/agentic-config repo for bugs and feature requests using GitHub CLI. Handles templates, explicit args, or extracts from conversation context. Invoke via /ac-issue.
Transforms error logs, screenshots, voice notes, and rough bug reports into structured GitHub issues with repro steps, environment details, impact severity, and evidence. Outputs MD files to /issues/.
Captures user-reported bugs as durable GitHub issues using the project's own domain language. Avoids stale references like file paths.