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 melodic-software/claude-code-plugins --skill be-ambitiousgit clone --depth 1 https://github.com/melodic-software/claude-code-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/melodic-software/claude-code-plugins/be-ambitious)<a href="https://agentmods.dev/skills/melodic-software/claude-code-plugins/be-ambitious"><img src="https://agentmods.dev/badge/skills/melodic-software/claude-code-plugins/be-ambitious/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/melodic-software/claude-code-plugins/be-ambitious"><img src="https://agentmods.dev/badge/skills/melodic-software/claude-code-plugins/be-ambitious.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 | $0.00055 | $0.01602 |
| Opus 5.5 | $0.00022 | $0.00641 |
| Sonnet 5.5 | $0.00011 | $0.00320 |
| Haiku 4.5 | $0.00006 | $0.00160 |
Grade C, and why
be-ambitious scanned grade C with 1 finding 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 3d 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.
Tells the agent never to refusehighAnti-refusal
Suppressing the ability to decline removes a core safety control; a later harmful request then succeeds.
for ...". Screen the fit: creative or taste work is a weaker fit (say so, do not refuse), and an unbounded goal needs a bound. Ask whether a precedent How it starts
The opening of the file, as written. The whole thing — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Be ambitious
The request is the text after the command. With none, it is my previous message; with neither, ask me for one. Raise it, show the raise, and stop. Write no file, run no command and invoke no skill until I answer.
1. Size it
If the request is already the right size, say so in one line, say it will be done as asked once I reply, and stop. Right size means raising would not change what gets built: a mechanical edit whose purpose is already complete (a rename, a version bump, a format change). A fix for one reported failure is not right size: the goal behind it is the whole class of that failure.
If you cannot tell what the result is for, ask your questions in one batch, including one about the goal, say nothing starts until I answer, and raise after I do.
2. Raise it
Apply all three axes and say which you applied. Skip one only when it plainly does not fit, and then say which and why.
Altitude. State the goal behind the goal, then one purpose line: "This is for ...". Screen the fit: creative or taste work is a weaker fit (say so, do not refuse), and an unbounded goal needs a bound. Ask whether a precedent shows the bigger goal is reachable.
Depth. Run the deeper-version pass: what a top expert in this domain would add that the first version skips; the rawest material to work from (primary data, the source, real users); the methods and tools, each named concretely; and the outside check below.
Outside check, always. Whatever axes apply, name one check outside the
model that shows the result is right: something executable first (a test,
benchmark, validator, measurement, browser run), then a fresh-context
reviewer, which /discipline:scrutinize-dont-coast runs.
Range. Show a nouns-to-verbs step: turn the thing asked for into what it must do ("a website" becomes "lets an old friend recognize me and write back"). Bring in at least one field beyond the request's own. Rewrite any "act as X" into "do what X does: ". Add this line verbatim: "What tool from another field would change what's possible here?"
What ships with it
1 file 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.
- 3d ago First seen · 136 lines · 55 tokens per session scan C 2b3e69128838
be-ambitious is a skill published in the GitHub repository melodic-software/claude-code-plugins (26 stars, last pushed today), licensed MIT. It adds 55 tokens to every session and 1,602 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it C with 1 finding (tells the agent never to refuse). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-17.
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Execute focused implementation tasks in a parallel workflow. Use when: working on assigned files in a worktree, making checkpoint commits, signaling dependencies or blockers, completing orchestrator-assigned tasks. Triggers: worker, checkpoint, worktree, assigned scope, commit prefix, parallel task.
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For NP-hard optimization: TSP, scheduling, assignment problems. Uses greedy construction + local improvement (2-opt, hill climbing).
solve-constraint-puzzle
For constraint satisfaction: Sudoku, scheduling, N-queens, logic puzzles, SAT-like problems, assignment problems. Uses propagate-then-search pattern.
test-with-examples
For example-driven development: test cases as specifications, input/output pairs, documentation through examples.
validate-before-process
For input validation: check format and constraints before processing, fail fast with clear errors, defensive parsing.