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/vladolaru/claude-code-plugins/sharpennpx skills add vladolaru/claude-code-plugins --skill sharpengit clone --depth 1 https://github.com/vladolaru/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/vladolaru/claude-code-plugins/sharpen)<a href="https://agentmods.dev/skills/vladolaru/claude-code-plugins/sharpen"><img src="https://agentmods.dev/badge/skills/vladolaru/claude-code-plugins/sharpen.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 | $0.00019 | $0.02208 |
| Opus 5 | $0.00010 | $0.01104 |
| Sonnet 5 | $0.00004 | $0.00442 |
| Haiku 4.5 | $0.00002 | $0.00221 |
Grade A, and why
sharpen 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 4d 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 — 207 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Codex Host Adapter
This skill is generated from the canonical Claude Code command named above. To execute it in Codex:
- Treat the text supplied after the skill mention as the invocation arguments. Substitute that exact text for
${CODEX_SKILL_ARGUMENTS}before executing shell commands. - Resolve
CODEX_PLUGIN_ROOTto the absolute plugin root. The loaded skill directory is<plugin-root>/codex-skills/<skill-name>, so the plugin root is two directories above the directory containing thisSKILL.md. - Assign both variables explicitly in any shell call that uses them. Codex does not export these instruction variables automatically.
- Use Codex's available user-input and subagent tools when the workflow requests them.
- Follow the canonical workflow below without skipping its gates or artifact checks.
Canonical Workflow
$dex:sharpen
Analyze agent behavior in the current conversation, find inefficiencies, and capture concrete fixes as project knowledge. This is an operational extraction strategy - it captures how the agent should work, not domain knowledge about the codebase.
digraph sharpen_flow {
"Start" [shape=doublecircle];
".claude/docs/ exists?" [shape=diamond];
"User wants scaffolding?" [shape=diamond];
"Create directories" [shape=box];
"Stop" [shape=doublecircle];
"Sub-agents dispatched?" [shape=diamond];
"Run analyzer" [shape=box];
"Scan conversation for inefficiencies" [shape=box];
"Inefficiencies found?" [shape=diamond];
"Nothing found - stop" [shape=doublecircle];
"Classify and draft fixes" [shape=box];
"Confirm with user" [shape=box];
"Write docs + update audit log" [shape=box];
"Any fix rule-worthy?" [shape=diamond];
"Offer promotion" [shape=box];
"Done" [shape=doublecircle];
"Start" -> ".claude/docs/ exists?";
".claude/docs/ exists?" -> "Sub-agents dispatched?" [label="yes"];
".claude/docs/ exists?" -> "User wants scaffolding?" [label="no"];
"User wants scaffolding?" -> "Create directories" [label="yes"];
"User wants scaffolding?" -> "Stop" [label="no"];
"Create directories" -> "Sub-agents dispatched?";
"Sub-agents dispatched?" -> "Run analyzer" [label="yes"];
"Sub-agents dispatched?" -> "Scan conversation for inefficiencies" [label="no"];
"Run analyzer" -> "Scan conversation for inefficiencies";
"Scan conversation for inefficiencies" -> "Inefficiencies found?";
"Inefficiencies found?" -> "Nothing found - stop" [label="no"];
"Inefficiencies found?" -> "Classify and draft fixes" [label="yes"];
"Classify and draft fixes" -> "Confirm with user";
"Confirm with user" -> "Write docs + update audit log" [label="accepted"];
"Confirm with user" -> "Stop" [label="skip"];
"Write docs + update audit log" -> "Any fix rule-worthy?";
"Any fix rule-worthy?" -> "Offer promotion" [label="yes"];
"Any fix rule-worthy?" -> "Done" [label="no"];
"Offer promotion" -> "Done";
}
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.
- 4d ago First seen · 207 lines · 19 tokens per session scan A 349af4bb38eb
sharpen is a skill published in the GitHub repository vladolaru/claude-code-plugins (8 stars, last pushed today), licensed MIT. It adds 19 tokens to every session and 2,208 once invoked, about $0.0001 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 2026-08-31.
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auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…