Install
$ agentstack add skill-tobihagemann-turbo-interpret-feedback ✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
About
Interpret Feedback
Run two independent interpretations of third-party feedback in parallel (internal + codex peer), then reconcile into enriched items with clear intent summaries. Designed for feedback where the author's intent is ambiguous or the correctness of suggestions is uncertain.
Step 1: Identify Feedback Items
Determine the feedback to interpret:
- If feedback items are in conversation context, use them
- If a file path or URL was provided, read or fetch the content
- If called by another skill, use the items passed in
For each item, collect whatever context is available: code snippets, diffs, surrounding discussion, file paths, line numbers. More context produces better interpretation.
Step 2: Run Two Interpretations in Parallel
Use the Agent tool to launch both agents below in a single assistant message so they run concurrently. Each Agent call uses model: "opus" and does not set run_in_background. That is two Agent tool calls total.
Internal Interpretation
Spawn a subagent with the feedback items and all available context. Instruct it to:
- Read all referenced code and surrounding context
- For each feedback item, produce:
- Intent: What the feedback author most likely wants changed and why (one to two sentences)
- Correctness: Whether the suggestion is technically sound — flag concerns if the reviewer may be mistaken, with evidence
- Ambiguity: Note where the intent is unclear or where multiple valid readings exist
- Return structured results per item
Run /peer-review Skill
Launch an Agent tool call whose prompt instructs the subagent to invoke /peer-review via the Skill tool. Describe the request in natural language:
- Material — the listed third-party feedback items and their surrounding context.
- Task — for each item, determine what the author most likely wants changed and why, whether the suggestion is technically sound, and where the phrasing is ambiguous enough to support multiple valid readings.
- Skepticism guidance — do not take feedback at face value. Check whether the author's stated concern matches the code reality. Look for cases where the reviewer misread the code, confused two similar constructs, or applied a general rule that does not fit this specific context.
- Output format — for each feedback item, return:
- Intent — what the author most likely wants changed and why (one to two sentences)
- Correctness — whether the suggestion is technically sound. If not, explain what the reviewer likely misunderstood, with evidence from the code
- Ambiguity — if the intent supports multiple valid readings, list each reading and which has stronger evidence
- Confidence — high (clear intent, sound suggestion), medium (likely intent but some uncertainty), or low (genuinely ambiguous or likely incorrect)
The prompt must also state explicitly that the subagent's final assistant message must contain the verbatim findings text /peer-review produced.
Step 3: Reconciliation
Merge the two interpretations for each feedback item:
| Agreement | Action | |-----------|--------| | Both agree on intent and correctness | High confidence. Use the shared interpretation. | | Intent agrees, correctness differs | Flag the correctness concern with both perspectives. | | Intent disagrees | Flag as ambiguous. Present both readings and note which has stronger evidence. |
Step 4: Output Enriched Items
For each feedback item, output the original feedback followed by the interpretation:
### Item :
**Original:**
**File:**
**Intent:**
**Correctness:** >
**Confidence:**
**Ambiguity:** >
After all items, add a summary:
## Interpretation Summary
- Total items:
- High confidence:
- Correctness concerns:
- Ambiguous intent:
Then use the TaskList tool and proceed to any remaining task.
Rules
- If either interpretation agent is unavailable or returns malformed output, proceed with results from the remaining agent.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: tobihagemann
- Source: tobihagemann/turbo
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.