If you use an AI agent that reads a primary instruction Markdown file (agent-specific; the agent will know the filename), integrate ORP by adding an ORP section to that file.
This makes ORP the agent’s default operating mode: explicit claim levels, reproducible verification, first-class failed paths, and dispute resolution by verification/downgrade (not debate).
If you are working inside an ORP-governed repo, ORP can also scaffold and maintain the repo's own AGENTS.md and
CLAUDE.md files:
orp initnow scaffolds them if missing and refreshes ORP-managed blocks if they already existorp agents syncrefreshes the ORP-managed blocks later without replacing surrounding human notesorp agents auditchecks whether those files are still alignedorp agents root set /absolute/path/to/projectsestablishes an optional umbrella parent directory so child repos can inherit high-level guidance
Do not let ORP process scaffolding masquerade as evidence or repository truth.
ORP should keep the agent honest about:
- where ongoing work lives
- whether the repo is in a safe state
- which secret or credential should be used
- where the work sits in the larger frontier
- when a checkpoint should be created
But evidence still lives in canonical project artifacts: code, data, logs, papers, proofs, outputs.
If the agent only remembers one ORP loop, it should be this:
- recover the workspace ledger
orp workspace tabs main
- inspect repo safety
orp status --json
- classify dirty worktree state before expansion
orp hygiene --json
- resolve the right secret
orp secrets ensure --alias <alias> --provider <provider> --current-project --json
- inspect the current frontier
orp frontier state --json
- if the work feels confusing or too large, break it down before moving
orp mode breakdown granular-breakdown --json
- do the next honest move
- checkpoint it honestly
orp checkpoint create -m "checkpoint note" --json
That is the ORP rhythm in one line:
- recover continuity
- inspect repo safety
- classify dirty state and stop if anything is unowned
- resolve access
- inspect context
- break down complexity when comprehension would help
- do the work
- checkpoint it honestly
Before deeper work, agents can discover ORP through three lightweight entry points:
docs/START_HERE.md— canonical human/operator onboarding path for local-first ORP usage.llms.txt— concise repo/package map for agents that scan docs before acting.orp about --json— machine-readable tool metadata, stable artifact paths, schemas, and available packs.orp pack list --json— machine-readable inventory of bundled packs.docs/AGENT_LOOP.md— canonical ORP operating rhythm for agent-led workflows.
Copy/paste this section into your agent’s main instruction Markdown file:
Non-negotiable boundary: ORP docs/templates are process-only and are not evidence. Evidence must live in canonical artifact paths (code/data/proofs/logs/papers).
- Always label claims as one of: Exact / Verified / Heuristic / Conjecture.
- If unsure, downgrade rather than overclaim.
- For Exact/Verified: include a Verification Hook (commands + expected outputs + determinism notes) and produce a Verification Record with PASS / FAIL / INCONCLUSIVE.
- If verification is FAIL: downgrade immediately and link the failure evidence.
- Treat failed paths as assets: record dead ends as a
Failed Path Recordwith the blocking reason/counterexample and a next hook. - Resolve disputes by verification or downgrade, not argument.
- Run
orp hygiene --jsonbefore long delegation, after material writeback, before remote side effects or unbudgeted paid compute, and when dirty state grows unexpectedly. - Do not hard-stop solely because an OpenAI research lane is paid; budgeted ORP research may run when
orp researchspend preflight is within the configured daily cap. - Stop long-running expansion while hygiene reports
dirty_unclassified; classify, refresh generated surfaces, canonicalize useful scratch, or write a blocker before continuing. - Hygiene is non-destructive: never reset, checkout, or delete files merely to hide dirty state.
- Before starting: read
PROTOCOL.mdand confirm the project’s Canonical Paths are defined. - When proposing a result: create/update a claim (via
templates/CLAIM.md) that points to canonical artifacts (not ORP docs). - When verifying: run the hook and write
templates/VERIFICATION_RECORD.md. - When something fails: write
templates/FAILED_TOPIC.mdand link it from the claim/issue.
- ORP may include optional Instruments under
modules/instruments/(e.g., Orbit / Compression / Adversarial). - Instruments are process-only and must not contain evidence/results. Verification remains blind to instruments.
- If an Instrument is used, note it in the claim’s Instrument (optional) section (name + parameters explored).
To prevent drift (especially after context compaction / summarization), re-check ORP and re-sync this block:
- at session start / new task,
- immediately after any context compaction/summarization,
- before publishing any Verified/Exact claim,
- after pulling/updating ORP files in the repo.
Sync procedure:
- Find the ORP root directory (the folder containing
PROTOCOL.md). - Ensure this ORP block matches
<ORP_ROOT>/AGENT_INTEGRATION.md(between<!-- ORP:BEGIN -->and<!-- ORP:END -->). - If out of date, sync it (script or manual):
<ORP_ROOT>/scripts/orp-agent-integrate.sh --sync /path/to/your/agent/instructions.md
Use the checkpoint tool to keep handoffs/compactions honest and to reduce “drift-by-forgetting” before git commit / git push.
- Command:
<ORP_ROOT>/scripts/orp-checkpoint.sh --sync --agent-file /path/to/your/agent/instructions.md "checkpoint note"
- Recommended moments:
- after context compaction/summarization or handoff
- before
git commit/git push - before publishing any Verified/Exact claim
This writes a process-only entry to <ORP_ROOT>/cone/CONTEXT_LOG.md and reports ORP snippet sync status.
If you want an automated insert into a file you specify, use:
./scripts/orp-agent-integrate.sh --sync /path/to/your/agent/instructions.mdTo check for drift (no changes), use:
./scripts/orp-agent-integrate.sh --check /path/to/your/agent/instructions.md