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 bjorn-ingmanson/thefroject-plugins --skill quarterly-plangit clone --depth 1 https://github.com/bjorn-ingmanson/thefroject-pluginsWrote 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/bjorn-ingmanson/thefroject-plugins/quarterly-plan)<a href="https://agentmods.dev/skills/bjorn-ingmanson/thefroject-plugins/quarterly-plan"><img src="https://agentmods.dev/badge/skills/bjorn-ingmanson/thefroject-plugins/quarterly-plan/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/bjorn-ingmanson/thefroject-plugins/quarterly-plan"><img src="https://agentmods.dev/badge/skills/bjorn-ingmanson/thefroject-plugins/quarterly-plan.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 | $0.00054 | $0.01023 |
| Opus 5.5 | $0.00022 | $0.00409 |
| Sonnet 5.5 | $0.00011 | $0.00205 |
| Haiku 4.5 | $0.00005 | $0.00102 |
Grade A, and why
quarterly-plan 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 2mo 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 — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Quarterly Plan
Set the 3-5 priorities that will define the quarter. Anything more is a wish list. Anything less probably misses something.
Gather Context First
- Read
context/roadmap.md(or equivalent) for longer-term direction - Read the prior
outputs/cadence/quarterly-review-*.mdif one exists - Scan the last 10-13
outputs/cadence/weekly-review-*.mdfor patterns and unfinished work - Check
context/project-vision.md(or equivalent) for the north star - Identify any external constraints (funding runway, team changes, market timing)
The Planning Sequence
Step 1 — Connect to the longer arc
Before naming priorities, articulate:
- Where we are — current state in one paragraph
- Where we're going — desired state by year-end
- What's missing — the gap between the two
Quarterly priorities exist to close the gap. If a candidate priority doesn't help close it, it's not a quarterly priority.
Step 2 — Generate candidates
List every plausible priority — 10-20 candidates. Don't filter yet.
Sources:
- Carry-forward from last quarter
- Patterns from the weekly reviews
- Strategic moves the roadmap implies
- Customer signals (transcripts, support, churn data)
- Team capacity and skill changes
- Market or competitor moves
Step 3 — Apply the priority filter
Score each candidate against four lenses:
| Lens | Question | Weight |
|---|---|---|
| Strategic value | Does this move us materially toward year-end? | 3x |
| Feasibility | Can we actually deliver this in 13 weeks with current capacity? | 2x |
| Reversibility | If wrong, can we course-correct? | 1x |
| Cost of inaction | What breaks if we don't do this? | 2x |
Cut the candidate list to top 8-10 by score. Then pick 3-5 from there.
Step 4 — Write priorities as outcomes
A priority is an outcome with a measurable definition of done.
| Weak (vision) | Strong (outcome) |
|---|---|
| "Improve activation" | "Lift week-1 activation from 31% to 45%" |
| "Better content" | "Publish 12 long-form pieces with 2k+ avg views" |
| "Hire faster" | "Close 3 senior roles by [end-of-quarter date]" |
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.
- 2mo ago First seen · 126 lines · 54 tokens per session scan A 976bc614d7ab
quarterly-plan is a skill published in the GitHub repository bjorn-ingmanson/thefroject-plugins (1 stars, last pushed 4mo ago), licensed MIT. It adds 54 tokens to every session and 1,023 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 2026-08-31.
quarterly-plan compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| quarterly-planbjorn-ingmanson/thefroject-plugins | Skill | 1 | 4mo ago | MIT | A | 54 | Claude Code |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | yesterday | MIT | A | 200 | Claude Code, Codex |
| playwright-climicrosoft/playwright | Skill | 100k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| browser-automationopenclaw/openclaw | Skill | 394k | today | MIT | A | 36 | Claude Code |
| systematic-debuggingobra/superpowers | Skill | 314k | 4d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |