Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/alivecontext/alive/load-contextnpx skills add alivecontext/alive --skill load-contextgit clone --depth 1 https://github.com/alivecontext/aliveWhat 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 | $0.00081 | $0.02815 |
| Opus 5 | $0.00041 | $0.01407 |
| Sonnet 5 | $0.00016 | $0.00563 |
| Haiku 4.5 | $0.00008 | $0.00281 |
Grade A, and why
alive:load-context 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 2d 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 — 265 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Load
Load a walnut. See where things are. Work.
Default: single-walnut focus. But people involved are loaded automatically (frontmatter only) — you can't work on a venture without knowing who's in it.
If No Walnut Named
Show available walnuts as a numbered list grouped by domain:
╭─ 🐿️ pick a walnut
│
│ Life
│ 1. identity active Mars visa application
│ 2. health quiet Sleep study results
│
│ Ventures
│ 3. nova-station active Orbital test window
│ 4. paper-lantern quiet Menu redesign
│
│ Experiments
│ 5. midnight-frequency active Episode 12 edit
│ 6. glass-cathedral waiting Decide: gallery or festival
│
│ ▸ Number to load, or name one.
╰─
Tier 1 — Brief Pack (3 files) + claim the session
Read these three files. That's it — everything you need to orient.
_kernel/key.md— full file (identity, people, links, rhythm)_kernel/now.json— full file (phase, bundle statuses with task summaries, recent sessions, nested walnut state, blockers, context paragraph)_kernel/insights.md— frontmatter only (what domain knowledge sections exist)- Claim this session for the walnut — Edit
.alive/_squirrels/{your-session-id}.yamland change thewalnut:field fromnullto the walnut's directory basename (e.g.walnut: berties,walnut: alive-os). Your session ID is in the SessionStart injection at the top of context (Session ID: ...); the squirrel YAML lives under the world's.alive/_squirrels/directory using the full UUID as the filename. This step is mandatory, not optional. Cross-session hooks (alive-context-watch.sh, the statusline,project.py's recent-sessions aggregator) all readwalnut:from this YAML to know which walnut you're on. If you skip this, parallel-session change detection silently no-ops, the statusline shows the wrong context, and projections under-count your activity. Use a single Edit withold_string: "walnut: null"andnew_string: "walnut: {name}". If the YAML already has a different walnut name (rare — cross-walnut session), leave it and surface the conflict to the human.
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.
- 2d ago First seen · 265 lines · 81 tokens per session scan A c173274084db
alive:load-context is a skill published in the GitHub repository alivecontext/alive (127 stars, last pushed 7d ago), licensed MIT. It adds 81 tokens to every session and 2,815 once invoked, about $0.0004 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 2026-08-30.
Other skills, from other repositories
crit-cli
Use when an agent needs to author or reply to crit inline comments programmatically (including multi-agent workflows commenting on shared code/plans/docs/proposals), publish or unpublish a crit review with crit share, sync a crit review to or from a GitHub PR or GitLab MR, or read/interpret a crit review JSON file.…
crit
Review code changes, a plan, a live page (running dev server), or a local HTML file with Crit inline comments and structured human feedback. Use only when the user explicitly invokes /crit or directly asks to use Crit; a generic review request does not count.
crit-story
Author a crit story only when the user explicitly invokes /crit-story or directly asks you to generate a crit story. Do not infer this skill from generic review, PR, or diff-review requests.
cco-budget
Configure token budget limits, auto-compact settings, and view current budget status (model-aware — Opus 4.8 default, full 1M context at standard price).
cco-config
View and tune CCO's behavior thresholds — re-read warnings, cache staleness, prompt-coach length bands, and the /cco-pack budget cap.
cco-overhead
Audit the fixed context overhead every session starts with — system prompt, MCP tools, agents, CLAUDE.md, memory — measured from real transcript usage.