956732d4a8
Eval probes wrote fixtures, receipts and evidence to hard-coded /tmp paths and two live A/B tasks literally instructed the model to work in /tmp. They now derive locations from tempfile.gettempdir() / os.tmpdir() (env overrides kept), usage examples use relative output names, and the desktop e2e screenshot dirs, perf scripts and the short-session repro fixture stop naming /tmp. Also adds the explicit encoding= the windows-footgun check wants in the touched files.
Tool Search live test harness
Runs five scenarios against a real model (Claude Haiku 4.5 via OpenRouter) to
verify that the bridge tools work end-to-end. Records transcripts in
evals/tool_search/out/.
Running
cd <repo root>
python3 evals/tool_search/tool_search_livetest.py # runs all 5 scenarios x 2 modes
python3 evals/tool_search/analyze_livetest.py # side-by-side report
Requires OPENROUTER_API_KEY set or present in ~/.hermes/.env.
What it verifies
| Scenario | Tests |
|---|---|
| A obvious_single | BM25 retrieval on an obvious tool name (github_create_issue) |
| B vague_paraphrased | Retrieval when the model has to paraphrase ("schedule meeting" → evt_create) |
| C multi_tool_chain | Multi-step task chaining two deferred tools (GitHub + Slack) |
| D core_plus_deferred | Mixed: core tool (read_file) called directly, deferred tool (Slack) via bridge |
| E no_tool_needed | Pure-knowledge prompt; verify no spurious tool_search invocations |
Each scenario runs with tool_search.enabled = on and again with off for an
A/B baseline. The harness records:
- bridge_calls (the tool_search / tool_describe / tool_call sequence the model emitted)
- underlying_tool_calls (what actually ran through the registry dispatcher)
- final_response, iteration count, elapsed time, any errors
Output structure
evals/tool_search/out/
<scenario>__enabled.json # tool_search ON
<scenario>__disabled.json # tool_search OFF
_summary.json # one-line summary across all runs
The 2026-05 baseline run is checked in for reference. Re-running may produce slightly different transcripts (the model is non-deterministic) but the expected_underlying_tools assertions should remain satisfied.