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/jumbocontext/cli/refine-jumbo-goalsnpx skills add jumbocontext/cli --skill refine-jumbo-goalsgit clone --depth 1 https://github.com/jumbocontext/cliWrote 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/jumbocontext/cli/refine-jumbo-goals)<a href="https://agentmods.dev/skills/jumbocontext/cli/refine-jumbo-goals"><img src="https://agentmods.dev/badge/skills/jumbocontext/cli/refine-jumbo-goals.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 | $0.00031 | $0.01580 |
| Opus 5 | $0.00015 | $0.00790 |
| Sonnet 5 | $0.00006 | $0.00316 |
| Haiku 4.5 | $0.00003 | $0.00158 |
Grade A, and why
refine-jumbo-goals 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 5d 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.
The source is not reproduced here
Licensed AGPL-3.0
The repository is licensed AGPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
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.
- 5d ago First seen · 175 lines · 31 tokens per session scan A b8b4ded61db4
refine-jumbo-goals is a skill published in the GitHub repository jumbocontext/cli (270 stars, last pushed 9d ago), licensed AGPL-3.0. It adds 31 tokens to every session and 1,580 once invoked, about $0.0002 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.
Other skills, from other repositories
backlog-management
Lorekeeper backlog management — ticket lifecycle, numbering, scripts, and conventions. Load this when filing tickets, moving ticket states, checking what's ready to work on, or onboarding to the project workflow.
lorekeeper-pm
PM workflow for Lorekeeper. Load when managing backlog, filing tickets, reviewing dev work, or planning features. For ticket lifecycle, numbering, and scripts, see backlog-management skill.
proposal-filing
File a new Lorekeeper proposal ticket — create markdown, create GitHub issue, commit, push. Use when requesting a new feature, filing a bug, or submitting a product idea.
sprint-review
Sprint review workflow — triage proposals, validate ticket readiness, and batch-promote tickets to dev. Load this before running a backlog review session.
product-owner
Scoping a product or feature, decomposing it into outcomes, epics, and stories, prioritizing a backlog, defining an MVP, mapping user journeys, or saying no to a stakeholder.
task-forest
Maintains a repo-local task forest or task DAG for the current workspace. Use when the user asks to initialize or update a task forest, close a session, summarize evolving project work, align a request with a global goal, track progress/history/deviations/todos, save or apply a task proposal, or export the…