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/nicknisi/sessions/weekly-summarynpx skills add nicknisi/sessions --skill weekly-summarygit clone --depth 1 https://github.com/nicknisi/sessionsWrote 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/nicknisi/sessions/weekly-summary)<a href="https://agentmods.dev/skills/nicknisi/sessions/weekly-summary"><img src="https://agentmods.dev/badge/skills/nicknisi/sessions/weekly-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 5.1 | $0.00060 | $0.00927 |
| Opus 5 | $0.00030 | $0.00464 |
| Sonnet 5 | $0.00012 | $0.00185 |
| Haiku 4.5 | $0.00006 | $0.00093 |
Grade A, and why
weekly-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 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 — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Generate a weekly summary of the user's AI coding sessions.
Steps
-
Get the date range. Calculate the start date (7 days ago) and end date (today) in YYYY-MM-DD format.
-
Fetch the digest. Call
get_activity_digestwith:startDate: 7 days agoendDate: todaydetail:"highlights"(first + last user messages for substantive sessions)
-
Review the digest. Read the response directly — do NOT send it to a subagent. The highlights mode is compact enough to process inline. For each day, identify:
- Which projects were worked on and what was accomplished
- Key decisions, pivots, or discoveries (visible in the first/last message pairs)
- Recurring themes across projects
-
Drill into key sessions (optional). If any sessions look particularly significant (high message count, interesting topic) but the highlights don't capture enough detail, call
get_session_messageson those specific sessions (up to 5) using thefilePathfrom the digest. -
Write the summary. Structure it as:
Week of {start} - {end}
By the numbers: {total sessions} sessions, {total messages} messages across {project count} projects.
Day-by-day: For each day with activity, write 2-4 bullet points capturing the most significant work. Be specific — name projects, features, and outcomes. Skip days with no meaningful activity.
Highlights: The 3-5 most significant accomplishments across the entire week.
Themes: Recurring work streams or focus areas (e.g., "SDK development", "infrastructure", "bug fixes").
-
Surface new memory candidates. Run
sessions memory mine --all --since-last --json, thensessions memory pending --json. The mine picks up only transcripts that changed since the last run, so this is cheap;--allis deliberate — a weekly summary spans every project, not whichever repo you happen to be sitting in.--alladvances the watermark for every repo, not just this one. That is the point (nothing gets skipped), but it means a latersessions memory mine --since-lastinside any single repo reports nothing changed until that repo's transcripts move again — this step has already mined them. Say nothing about it here; it is noted so the interaction is not rediscovered as a bug.pendingprints{"count": N, "preview": [{"id", "text"}]}. If the count is zero, say nothing. Do not add an empty section, do not write "no new memory", do not mention that you checked. Most weeks have nothing, and a recurring empty section trains the user to skim past the whole summary.Otherwise close the summary with a short block: the count, up to three candidate texts from the preview (the preview holds five; showing three is deliberate), and one line saying to run
/memoryto triage. Do not triage here and never approve, reject, or snooze anything — this is a nudge, not the workflow.This step must never damage the summary. Unlike
/memory, which stops loudly when the binary is missing, this one fails silently: ifsessionsis not installed, either command exits non-zero, or the output does not parse, skip the block entirely and finish the summary as written. The summary already succeeded before this step ran.
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 · 59 lines · 60 tokens per session scan A 6570d07a156b
weekly-summary is a skill published in the GitHub repository nicknisi/sessions (30 stars, last pushed 4d ago), licensed MIT. It adds 60 tokens to every session and 927 once invoked, about $0.0003 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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