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 mshadmanrahman/pm-pilot --skill weekly-statusgit clone --depth 1 https://github.com/mshadmanrahman/pm-pilotWrote 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/mshadmanrahman/pm-pilot/weekly-status)<a href="https://agentmods.dev/skills/mshadmanrahman/pm-pilot/weekly-status"><img src="https://agentmods.dev/badge/skills/mshadmanrahman/pm-pilot/weekly-status/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/mshadmanrahman/pm-pilot/weekly-status"><img src="https://agentmods.dev/badge/skills/mshadmanrahman/pm-pilot/weekly-status.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00058 | $0.00856 |
| Opus 5.5 | $0.00023 | $0.00342 |
| Sonnet 5.5 | $0.00012 | $0.00171 |
| Haiku 4.5 | $0.00006 | $0.00086 |
Grade A, and why
weekly-status 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.
How it starts
The opening of the file, as written. The whole thing — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Weekly Status
Generates a structured weekly accomplishment report by pulling activity from all connected work tools. Covers what got done, key metrics, blockers, and upcoming priorities.
When to Activate
- User says "weekly status", "status report", "weekly update"
- User asks "what did I do this week?" or "what did I accomplish?"
- User needs to prepare for a standup, skip-level, or weekly sync
Input
Optional overrides:
- Date range: Defaults to last 7 days. User can specify "last 2 weeks" or specific dates.
- Focus area: Limit to a specific project, team, or epic.
- Audience: "for my manager", "for the team", "for skip-level" (adjusts detail level).
Execution
Step 1: Determine Date Range
Default: 7 days back from today. Use the system date command to get the current date.
Step 2: Parallel Data Gathering (Fan-Out)
Launch parallel searches across all connected MCP sources.
| Source | Query | Extract |
|---|---|---|
| Jira | Issues transitioned to Done/Closed in date range, assigned to user | Completed work, story points |
| Jira | Issues currently In Progress, assigned to user | Active work |
| Jira | Issues with blockers or impediments | Blockers |
| GitHub | PRs merged by user in date range | Code shipped |
| GitHub | PRs opened and still in review | Pending reviews |
| Confluence | Pages created or updated by user in date range | Documentation work |
| Slack | Threads where user posted substantive messages | Key discussions, decisions |
Step 3: Categorize and Synthesize
Group findings into categories:
- Shipped: Completed Jira issues, merged PRs, published docs
- In Progress: Active issues, open PRs
- Blocked: Issues with impediments, stalled PRs
- Discussions: Key decisions made in Slack/email
Step 4: Generate Report
Output Format
Output directly in conversation (do NOT create a file unless asked):
# Weekly Status: {Date Range}
## Accomplishments
### Shipped
- {Completed item} ({source}: {link or ID})
- {Completed item} ({source}: {link or ID})
### Documentation
- {Page created/updated} ({Confluence link})
### Decisions Made
- {Decision}: {context} ({Slack channel or meeting})
## Metrics
- Issues completed: {count} ({story points} points)
- PRs merged: {count}
- Pages published: {count}
## In Progress
- {Active item}: {status/next step} ({source})
## Blockers
- {Blocker}: {what's needed to unblock} ({source})
## Next Week
- {Priority 1}: {brief description}
- {Priority 2}: {brief description}
- {Priority 3}: {brief description}
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 · 105 lines · 58 tokens per session scan A c0aef2793043
weekly-status is a skill published in the GitHub repository mshadmanrahman/pm-pilot (22 stars, last pushed 23d ago), licensed MIT. It adds 58 tokens to every session and 856 once invoked, about $0.0002 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 2026-08-30.
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