llms.txt · git:20260913.4275b80 · 2026-09-13 · sha256 ee11820f08470021
llms.txt git:20260913.4275b80A
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# hermes-blind
> Dependency-free prompt and session-recovery scaffolds for LLM workflows.
## Public surface
- `wrap(prompt, variant="v1")`: prepend an evidence-gating evaluation prefix.
- `extract_disclosure(response)`: parse an optional disclosure line.
- `hermes-blind apply --session ...`: extract a turn-one goal anchor from
Claude Code or Codex JSONL.
- `compose_intent(...)`: add optional intent-debias and scope-class framing.
The package is deterministic. It makes no model calls and no network requests.
## Install
pip install hermes-blind
## Recovery example
hermes-blind apply --session rollout.jsonl --format auto \
--anchor-mode goals --turn 9 --out recovery.md
`--turn` is metadata, not a detector threshold. Recovery output may contain
user text and should be reviewed before sharing.
## Find a supported session log
Blind reads an explicit local JSONL path and currently supports Claude Code
and Codex session logs:
ls -t ~/.claude/projects/*/*.jsonl | head
find ~/.codex/sessions -type f -name 'rollout-*.jsonl' -print 2>/dev/null | sort | tail
Gemini CLI installs expose the package's prompt and skill surfaces; Gemini
session-log recovery is not currently supported.
## Evidence boundary
The 0.1.3 release validates package mechanics, JSONL parsing, anchor modes,
build/install behavior, and CLI operation. In a frozen 66-goal extraction
audit, goal-set extraction retained 40 goals versus 7 for the prior
first-sentence heuristic.
That result does not establish downstream drift recovery. Bias reduction,
behavioral recovery, automatic drift detection, optimal timing, adversarial
robustness, and non-English behavior remain unproven.
0.1.3 is the first public 0.1.x release; public delta: 0.0.6 → 0.1.3.
Repository: https://github.com/hermes-labs-ai/hermes-blind
License: MIT