Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/terrene-foundation/kailash-coc-claude-pynpx agentmods add commands/terrene-foundation/kailash-coc-claude-py/codifyWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/terrene-foundation/kailash-coc-claude-py/codify)<a href="https://agentmods.dev/commands/terrene-foundation/kailash-coc-claude-py/codify"><img src="https://agentmods.dev/badge/commands/terrene-foundation/kailash-coc-claude-py/codify/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/terrene-foundation/kailash-coc-claude-py/codify"><img src="https://agentmods.dev/badge/commands/terrene-foundation/kailash-coc-claude-py/codify.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00025 | $0.05041 |
| Opus 5 | $0.00013 | $0.02521 |
| Sonnet 5 | $0.00005 | $0.01008 |
| Haiku 4.5 | $0.00003 | $0.00504 |
Grade A, and why
codify scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Workspace Resolution
- If
$ARGUMENTSspecifies a project name, useworkspaces/$ARGUMENTS/ - Otherwise, use the most recently modified directory under
workspaces/(excludinginstructions/) - If no workspace exists, ask the user to create one first
- Read all files in
workspaces/<project>/briefs/for user context (this is the user's input surface)
Phase Check
- Read
workspaces/<project>/04-validate/to confirm validation passed - Read
docs/anddocs/00-authority/for knowledge base - Output: update existing agents and skills in their canonical locations. Which locations exist depends on the repo's tier subscriptions — Kailash-subscribing targets carry the framework trees (
agents/frameworks/,skills/01-core-sdk/,skills/02-dataflow/, …); a stack-agnostic base template carries none of them, so codify into the agent/skill trees that repo actually has.
Execution Model
This phase executes under the autonomous execution model (see rules/autonomous-execution.md). Knowledge extraction and codification are autonomous — agents extract, structure, and validate knowledge without human intervention. The human reviews the codified output at the end (structural gate on what becomes institutional knowledge), but the extraction and synthesis process is fully autonomous.
Workflow
0. Acquire codify lease (multi-operator concurrency gate)
Per (loom-internal reference) §7.1: two concurrent /codify invocations clobber the rule corpus. Acquire the lease BEFORE any step below.
Call acquireCodifyLease({ scopeFiles, displayId }) from .claude/hooks/lib/codify-lease.js. The helper unions .claude/learning/learning-codified.json + .claude/.proposals/latest.yaml into the scope automatically. displayId comes from operator-id.js::resolveIdentity().
On { ok: false, reason: "conflict" }: STOP, surface the conflicting display_id + acquired_at + scope overlap to the user verbatim, plus liveness.basis (why the lease is still judged HELD). Silent proceed is BLOCKED (rules/zero-tolerance.md Rule 3). Conversely, an { ok: true } carrying reclaimed means this acquire TOOK OVER a lease a crashed/abandoned session never released (age past the 12h LEASE_TTL_MS floor) — surface reclaimed.display_id + reclaimed.acquired_at + reclaimed.liveness.basis verbatim, and reclaimed.record_emit when it is not ok. reclaimed is absent on every normal acquire; a takeover the operator never sees is indistinguishable from the clobber the lease exists to prevent.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 152 lines · 25 tokens per session scan A c9e1ccd02d5f
codify is a command published in the GitHub repository terrene-foundation/kailash-coc-claude-py (12 stars, last pushed 21d ago), licensed Apache-2.0. It adds 25 tokens to every session and 5,041 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.