Debug Stuck Hawk/Inspect AI Evaluations

VerifiedCaution

Diagnoses why a Hawk/Inspect AI evaluation is stuck or not progressing. Provides a checklist, error pattern lookup, and direct API testing to identify issues like API retries, pod crashes, or token limits. Helps recover by deleting and restarting the eval or inspecting logs.

Sby Skills Guide Bot
TestingIntermediate
706/2/2026
Claude Code
#debugging#stuck-evals#hawk#inspect-ai#evaluation

Recommended for

Our review

Provides a systematic approach to debug stuck Hawk/Inspect AI evaluations, covering auth checks, pod status, logs, and direct API testing.

Strengths

  • Offers a structured checklist to quickly identify the root cause of stuck evals.
  • Includes advanced techniques such as direct API calls and retry pattern analysis.
  • Provides concrete resolutions for each documented error pattern.

Limitations

  • Requires access to internal Hawk tools and S3 infrastructure.
  • Solutions depend on the specific environment configuration (middleman, providers).
  • Does not cover underlying infrastructure issues (network, API quotas).
When to use it

When a Hawk/Inspect AI evaluation is not progressing, samples remain incomplete, or 500 errors occur.

When not to use it

For evaluation issues not related to stalling, such as task logic or scoring errors.

Security analysis

Caution
Quality score92/100

The skill instructs authenticated access to internal services and deletion of resources, but within a legitimate debugging context. It does not exfiltrate data, run destructive system commands, or disable safety. Risk is limited to users with existing authorization.

Findings
  • Uses `curl` to test internal API endpoints with access tokens.
  • Instructs deletion of evaluation sets via `hawk delete`.
  • References internal infrastructure (middleman.internal.metr.org) and proprietary tools.

Examples

Debug stuck eval
My Inspect eval is stuck. The eval-set ID is evalset-abc123. Can you help me debug it?
Investigate high retry count
I see 'HTTP retries: 45' in my eval logs. What does that mean and how do I fix the stuck eval?
Test API directly
I'm getting 500 errors from the middleman during an eval. How do I test the API directly to see the real error?

name: debug-stuck-eval description: Debug stuck Hawk/Inspect AI evaluations. Use when user mentions "stuck eval", "eval not progressing", "eval hanging", "samples not completing", "eval set frozen", "runner stuck", "500 errors in eval", "retry loop", "eval timeout", or asks why an evaluation isn't finishing.

Quick Checklist

  1. Verify auth: hawk auth access-token > /dev/null || echo "Run 'hawk login' first"
  2. Get eval-set-id from user
  3. Check status: hawk status <eval-set-id> - JSON report with pod state, logs, metrics
  4. View logs: hawk logs <eval-set-id> or hawk logs -f for follow mode
  5. List samples: hawk list samples <eval-set-id> - see completion status
  6. Look for error patterns (see below)
  7. Test API directly if logs show retries without clear errors

Error Patterns

| Log Pattern | Meaning | Resolution | |-------------|---------|------------| | [uuid task/id/epoch model] Retrying request to /responses | OpenAI SDK retry with sample context | Test API directly with curl to see real error | | [uuid task/id/epoch model] -> model retry N ... [ErrorType code] | Inspect retry with error summary | Check error type; use curl for full details | | 500 - Internal server error | API issue | Download buffer, find failing request, test through middleman AND directly to provider | | 400 - invalid_request_error | Token/context limit exceeded | Check message count and model context window | | Pod UID mismatch | Sandbox pod was killed and restarted | No fix needed—sample errored out, Inspect will retry | | Empty output, pending: true | API returned malformed response | Restart eval (buffer resumes) | | OOMKilled in pod status | Memory exhaustion | Increase pod memory limits |

Key Techniques

  1. Retry messages have sample context - All retry messages include a [sample_uuid task/sample_id/epoch model] prefix. Inspect's own retries also include a compact error summary suffix like [RateLimitError 429 rate_limit_exceeded]. The OpenAI SDK's internal retry messages still don't show the actual error — use curl for full details.
  2. FAIL-OK patterns are fine - Alternating failures and successes mean the eval IS progressing. Only worry about consistent FAIL-FAIL-FAIL patterns.
  3. Use S3 for buffer access - Download .buffer/ from S3 rather than accessing the runner pod directly.
  4. Read .eval files with inspect_ai - Use from inspect_ai.log import read_eval_log instead of manually extracting zips.

Test API Directly

Middleman is the auth proxy. If middleman fails but direct provider calls work, it's a middleman issue.

TOKEN=$(hawk auth access-token)

# Test through middleman
curl --max-time 300 -X POST https://middleman.internal.metr.org/anthropic/v1/messages \
  -H "Authorization: Bearer $TOKEN" -H "Content-Type: application/json" \
  -d '{"model": "claude-sonnet-4-20250514", "max_tokens": 100, "messages": [{"role": "user", "content": "Say hello"}]}'

# Test OpenAI-compatible
curl --max-time 300 -X POST https://middleman.internal.metr.org/openai/v1/chat/completions \
  -H "Authorization: Bearer $TOKEN" -H "Content-Type: application/json" \
  -d '{"model": "gpt-4o", "messages": [{"role": "user", "content": "Say hello"}], "max_tokens": 100}'

Recovery

# Delete stuck eval and restart
hawk delete <eval-set-id>
hawk eval-set <config.yaml>

The sample buffer in S3 allows Inspect to resume from where it left off (unless you use --no-resume).

HTTP Retry Count

Task progress logs include "HTTP retries: X". High retry counts indicate API instability even while tasks complete.

Severity: Retry count × wait time = stuck duration. E.g., 45 retries × 1800s = 22+ hours stuck.

More Details

See docs/debugging-stuck-evals.md for:

  • Sample buffer SQL queries
  • Detailed API testing examples
  • Escalation checklist

References

Filing Issues

  • Middleman: https://github.com/metr-middleman/middleman-server/issues
  • Hawk: Linear issue on Evals Execution team
  • Inspect AI: https://github.com/UKGovernmentBEIS/inspect_ai/issues
Related skills