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 MSApps-Mobile/claude-plugins --skill make-plangit clone --depth 1 https://github.com/MSApps-Mobile/claude-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/msapps-mobile/claude-plugins/make-plan)<a href="https://agentmods.dev/skills/msapps-mobile/claude-plugins/make-plan"><img src="https://agentmods.dev/badge/skills/msapps-mobile/claude-plugins/make-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/msapps-mobile/claude-plugins/make-plan"><img src="https://agentmods.dev/badge/skills/msapps-mobile/claude-plugins/make-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 | $0.00086 | $0.00527 |
| Opus 5.5 | $0.00034 | $0.00211 |
| Sonnet 5.5 | $0.00017 | $0.00105 |
| Haiku 4.5 | $0.00009 | $0.00053 |
Grade A, and why
make-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 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
make-plan: Memory-Grounded Planning
A good plan starts from the current state, not a blank slate. Memory tells you what's been decided, what's blocking progress, and what was left mid-session.
Planning Workflow
1. Load context from memory
# What was done recently?
python3 {SKILL_DIR}/scripts/memory_store.py timeline --hours 168 --limit 30
# What's in progress / blocked?
COWORK_MEM_DB=~/mnt/.claude/.cowork-mem/memory.db \
python3 {SKILL_DIR}/scripts/vector_search.py "in progress blocked next step" --limit 10
# What did the last session summary say?
python3 {SKILL_DIR}/scripts/memory_store.py search "session summary" --type summary --limit 5
2. Check for known errors or constraints
python3 {SKILL_DIR}/scripts/memory_store.py search "error bug blocked" --type error --limit 5
3. Build the plan
Structure the plan as:
- Context: What we know from memory (1-3 bullets, specific)
- Goal: What we're trying to accomplish
- Steps: Numbered, specific, actionable — reference actual files and systems
- Blockers: Known issues from memory that affect the plan
- Open questions: Things we'd need to investigate
4. Save the plan as a decision
python3 {SKILL_DIR}/scripts/memory_store.py add decision \
"Plan: <summary of steps>" --tags "plan,session-goal"
Planning Tips
- Plans built from memory are more accurate than plans from scratch — use it
- Surface blockers from memory explicitly; don't let them be surprises mid-sprint
- If memory has conflicting decisions, flag it for the user to resolve
- Short plans (3-5 steps) are better than exhaustive ones — you can always plan the next thing after
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 · 57 lines · 86 tokens per session scan A 53db7951be42
make-plan is a skill published in the GitHub repository MSApps-Mobile/claude-plugins (10 stars, last pushed today), licensed MIT. It adds 86 tokens to every session and 527 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.
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