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 skills add iwe-org/dev-workspace --skill weeklygit clone --depth 1 https://github.com/iwe-org/dev-workspaceWrote 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/skills/iwe-org/dev-workspace/weekly)<a href="https://agentmods.dev/skills/iwe-org/dev-workspace/weekly"><img src="https://agentmods.dev/badge/skills/iwe-org/dev-workspace/weekly/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/skills/iwe-org/dev-workspace/weekly"><img src="https://agentmods.dev/badge/skills/iwe-org/dev-workspace/weekly.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 | $0.00071 | $0.00474 |
| Opus 5.5 | $0.00028 | $0.00190 |
| Sonnet 5.5 | $0.00014 | $0.00095 |
| Haiku 4.5 | $0.00007 | $0.00047 |
Grade A, and why
weekly 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 1mo 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
Weekly digest
A read-only sweep of the graph that answers: what moved, what's stuck, what's next. Numbers come from frontmatter and git — never from memory.
Steps
- Shipped. Plans completed in the last 7 days:
iwe find --filter '{stage: done}' --included-by data/plans -f jsonand keep those with acompleteddate in range; cross-check withgit log --since '7 days ago' --oneline. List releases cut, if any. - In flight. Active plans (no
stage) under## Activeindata/plans.md; flag any untouched for 14+ days (last commit touching the file) as possibly stalled or silently done. - Open bugs. Docs under
data/bugs.mdwithoutstage: done/cancelled. - Backlog head.
## Highitems indata/backlog.md, plus how long they've sat (created). - Graph health.
iwe schema validate(report violations) andiwe stats(dangling links, plus anydata/document listed under Orphans other thandata/index— every content doc should be reachable from a hub). Healthy means zero of each. - Print the digest — shipped / in flight / bugs / backlog / health — and end with the single most leveraged next action, chosen from what the sweep showed, with a one-line justification.
Rules
- Read-only: this skill writes no files and changes no statuses; if the sweep finds inconsistencies (a done plan still under Active), report them as the next action instead of fixing silently.
- Every number in the digest traces to a query or git — no estimates.
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.
- 1mo ago First seen · 37 lines · 71 tokens per session scan A 80ea11798bed
weekly is a skill published in the GitHub repository iwe-org/dev-workspace (10 stars, last pushed 2mo ago), licensed MIT. It adds 71 tokens to every session and 474 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-08-31.
Other skills, from other repositories
create-issue
Draft and submit a GitHub issue from a user idea or bug description, with bilingual body and correct labels.
agent-state-bar
A design guide for an agent status bar: a short, automatically updated summary of progress, remaining tasks, tool counts, errors, and system state placed near the latest model input.
reward-design
A guide to defining the scores that an AI agent receives during trial-and-error training. It covers checks based on rules, human preferences, or another model, and distinguishes rewarding the final result from rewarding the steps taken.
gh-file-issue
Use when filing a new Codewhale GitHub issue: turn a bug or idea into a well-formed, actionable issue with repro, acceptance criteria, labels, and milestone.
gh-treasure-hunt
Hunt the issue/PR queue for highest value-over-risk wins: clean focused community PRs, already-implemented issues to close, safe quick-fixes.
ai-style
A Chinese-language writing guide for producing or revising reader-facing text such as product announcements, public-account articles, emails, and README files. It focuses on reducing patterns that make writing sound machine-generated.