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/runbear-io/aweek/summarynpx skills add runbear-io/aweek --skill summarygit clone --depth 1 https://github.com/runbear-io/aweekWrote 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/runbear-io/aweek/summary)<a href="https://agentmods.dev/skills/runbear-io/aweek/summary"><img src="https://agentmods.dev/badge/skills/runbear-io/aweek/summary.svg" alt="Measured on agentmods" 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 | $0.00022 | $0.01155 |
| Opus 5 | $0.00011 | $0.00577 |
| Sonnet 5 | $0.00004 | $0.00231 |
| Haiku 4.5 | $0.00002 | $0.00115 |
Grade A, and why
summary 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 4d 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 — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
aweek:summary
Display a one-screen dashboard for every aweek agent. Each row shows the agent's name, goal count, weekly task progress, token-budget usage, and current lifecycle state.
This skill is read-only — it never mutates agent data.
Instructions
Follow this exact workflow when invoked. Use the project's Node.js modules
in src/skills/summary.js — never read agent JSON files directly.
Step 1: Gather and render the dashboard
Run:
echo '{"dataDir":".aweek/agents"}' \
| aweek exec summary buildSummary --input-json -
The JSON result exposes result.report (the formatted table) and
result.agentCount. Present the formatted output from result.report
directly to the user.
Do not paraphrase or re-order columns — the table is intentionally compact.
Step 2: Offer drill-down (only when agents exist)
Do not volunteer the detail view automatically — keep the first screen
focused on the dashboard table. When result.agentCount === 0, skip this
step entirely.
2a. Fetch drill-down choices
Call getAgentDrillDownChoices to build a homogeneous list of options for
the prompt (every real agent plus a synthetic No thanks entry with
id: null):
echo '{"dataDir":".aweek/agents"}' \
| aweek exec summary getAgentDrillDownChoices --input-json -
2b. Ask which agent to inspect
Use AskUserQuestion with the labels from the previous step. The
recommended phrasing: "Inspect a specific agent in detail?"
- Map each choice's
labelto an answer option. - The
No thanksentry (withid: null) is always the last option — select it to end the skill without any detail view.
2c. Render the detail block
If the user picks a real agent, call buildAgentDrillDown with its id
and print result.report verbatim:
echo '{"dataDir":".aweek/agents","agentId":"<id-from-the-user>"}' \
| aweek exec summary buildAgentDrillDown --input-json -
The returned JSON has a report field — print it verbatim.
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.
- 4d ago First seen · 130 lines · 22 tokens per session scan A 730e3642b35a
summary is a skill published in the GitHub repository runbear-io/aweek (11 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 22 tokens to every session and 1,155 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 2026-08-30.
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