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 commands/kouroshez/coding-os/dailygit clone --depth 1 https://github.com/kouroshez/coding-osWhat 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 | $0.00000 | $0.00304 |
| Opus 5 | $0.00000 | $0.00152 |
| Sonnet 5 | $0.00000 | $0.00061 |
| Haiku 4.5 | $0.00000 | $0.00030 |
Grade A, and why
daily 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.
What it actually says
Run the Scrumban daily standup view and present a structured summary.
Steps:
- Call MCP tool
cos_task_daily(canonical source — already aggregates yesterday / today / blocked / WIP / streak). - Render in the template below (matches
task-driverskill conventions). Use information ONLY from the tool envelope — do not fabricate task IDs or titles. - End with the next-action recommendation: which task should be picked up next, based on
cos_task_pick.
Template:
## Daily — YYYY-MM-DD
### Yesterday
- [TASK-NNN] {title} → moved to {status}, {one-line outcome}
### Today (candidates)
- [TASK-NNN] {title} ({swimlane}/{kind}, priority {P})
### Blocked
- [TASK-NNN] {title} — blocker: {reason}, since {date}
### WIP check
- in_progress: {n}/cap{cap}
- testing: {n}/cap{cap}
- violations: {none | list}
### Recommended next: TASK-NNN — {one-line reason}
If cos_task_daily returns empty (no tasks ever created), explain that the board is empty and offer to create a task via cos_task_create.
ADHD-friendly default: silent on broken streaks (per task-driver "Daily streak ≠ shame"). Only surface if the user asks.
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 · 32 lines · 0 tokens per session scan A 9cf4ba46268b
daily is a command published in the GitHub repository kouroshez/coding-os (6 stars, last pushed 2d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 304 tokens. 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 2026-08-31.
Other commands, from other repositories
export
Export a knowledge abstract to an Obsidian vault — a folder of Markdown notes linked by [[wikilinks]].
info
Display information and statistics about a knowledge abstract.
wh:llmsr-transfer
Use when the user wants to test whether an LLM-SR discovered equation's FORM generalizes to a recording the search never scored, and ingest both transfer numbers into the Wheeler knowledge graph.
wh:resume
Use when starting a new session and restoring Wheeler context from STATE.md or .plans/.continue-here.md.
maestro-next
Unified entry for all development intents — classify intent, assess complexity, route to the correct execution channel: /maestro-companion (lightweight), standard single run, or /maestro and /maestro-ralph (multi-step manual/orchestrated). Pure router, never runs execution loops itself.
analyze-task
Parse user task description -> detect required capabilities -> build dependency graph -> design dynamic roles with role-spec metadata. Outputs structured task-analysis.json with frontmatter fields for role-spec generation.