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 Orkas-AI/Orkas-Awesome-AgentSkills --skill study-plannergit clone --depth 1 https://github.com/Orkas-AI/Orkas-Awesome-AgentSkillsWrote 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/orkas-ai/orkas-awesome-agentskills/study-planner)<a href="https://agentmods.dev/skills/orkas-ai/orkas-awesome-agentskills/study-planner"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas-awesome-agentskills/study-planner/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/orkas-ai/orkas-awesome-agentskills/study-planner"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas-awesome-agentskills/study-planner.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 | $0.00003 | $0.01523 |
| Opus 5 | $0.00002 | $0.00762 |
| Sonnet 5 | $0.00001 | $0.00305 |
| Haiku 4.5 | $0.00000 | $0.00152 |
Grade A, and why
study-planner 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 12d 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 — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Study Planner
When To Use
- The user wants a concrete study or exam-prep schedule from a goal, deadline, current level, available time, and weak areas.
- The user wants to revise an existing plan after falling behind, changing the deadline, adding tasks, blocking weekdays, or reducing the daily budget.
- The user asks for check-ins, weekly reports, spaced review, revision checkpoints, or a plan that keeps them accountable.
Do not use for homework tutoring, solving practice problems, generating full course content, generating a full question bank, thesis coaching, material organization, medical/fitness/mental-health plans, or legal/business advice. If the user asks for practice tasks, keep them at the schedule level and use references/retrieval-task-patterns.md; do not author an entire worksheet or quiz set.
How To Call
- Collect the required planning fields: measurable goal, deadline, current level, weekday/weekend time budget, and weak areas. If any required field is missing, ask only for the missing fields before drafting the plan.
- Confirm optional fields when relevant: existing materials/resources, preferred time granularity, report format, fixed unavailable days, reminder preference, and whether the user wants files saved.
- Select the plan shape with
references/planning-workflow.md: short sprint, exam prep, long-term learning, skill acquisition, or revision recovery. - Select methodology rules with
references/methodology.md: spaced review, Pareto prioritization, Pomodoro task sizing, and Feynman-style output. - Add spaced review slots with
references/spaced-practice.mdwhenever the plan involves memorization, exams, concepts, formulas, vocabulary, procedures, or long-term retention. - If the plan includes review starters or active recall work, use
references/retrieval-task-patterns.mdto schedule task types only. Do not generate a full set of questions unless the user explicitly asks for practice materials. - Generate the plan progressively:
- For plans longer than 4 weeks, first show phases, weekly/monthly goals, milestones, and workload fit. Ask whether to expand weekly details.
- For plans of 4 weeks or less, it is acceptable to show all daily tasks if the workload is manageable.
- Before presenting a final daily schedule, run the workload self-check in
references/plan-quality-rules.md: daily task time must leave buffer, each task must be checkable, single tasks must be short enough, and weak areas must be weighted. - When the user changes an existing plan, preserve prior progress by default. Ask whether they want to adjust the current plan or start a new plan if the wording is ambiguous.
- For reminders, check-ins, and weekly reports, use
references/checkins-and-adjustments.md. Create or update reminders only when the user confirms the plan and wants reminder support.
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 163 lines · 3 tokens per session scan A e31a2a2af51b
study-planner is a skill published in the GitHub repository Orkas-AI/Orkas-Awesome-AgentSkills (13 stars, last pushed 2mo ago), licensed MIT. It adds 3 tokens to every session and 1,523 once invoked, about $0.0000 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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