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 terrylica/cc-skills --skill augmentgit clone --depth 1 https://github.com/terrylica/cc-skillsWrote 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/terrylica/cc-skills/augment)<a href="https://agentmods.dev/skills/terrylica/cc-skills/augment"><img src="https://agentmods.dev/badge/skills/terrylica/cc-skills/augment.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00032 | $0.00681 |
| Opus 5 | $0.00016 | $0.00341 |
| Sonnet 5 | $0.00006 | $0.00136 |
| Haiku 4.5 | $0.00003 | $0.00068 |
Grade A, and why
augment scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Augment Kokoro TTS
Upgrade MLX-Audio dependencies, re-download the model, and update bundled scripts.
Self-Evolving Skill: This skill improves through use. If instructions are wrong, parameters drifted, or a workaround was needed — fix this file immediately, don't defer. Only update for real, reproducible issues.
Workflow
Step 1: Pre-upgrade health check
ROOT="$(cc-plugin-root kokoro-tts)"
bash "$ROOT/scripts/kokoro-install.sh" --health
cat ~/.local/share/kokoro/version.json
Step 2: Execute upgrade
ROOT="$(cc-plugin-root kokoro-tts)"
bash "$ROOT/scripts/kokoro-install.sh" --upgrade
This upgrades:
- Python packages:
mlx-audio,soundfile,numpy - Model weights: re-downloaded from
mlx-community/Kokoro-82M-bf16 - Bundled scripts:
kokoro_common.pyandtts_generate.pyre-copied from plugin version.json: rewritten with new versions
Step 3: Post-upgrade verification
ROOT="$(cc-plugin-root kokoro-tts)"
bash "$ROOT/scripts/kokoro-install.sh" --health
cat ~/.local/share/kokoro/version.json
# Test synthesis
~/.local/share/kokoro/.venv/bin/python ~/.local/share/kokoro/tts_generate.py \
--text "Upgrade verification" --voice af_heart --lang en-us --speed 1.0 \
--output /tmp/kokoro-upgrade-test.wav && echo "OK"
Rollback
If upgrade breaks TTS, do a clean reinstall:
ROOT="$(cc-plugin-root kokoro-tts)"
bash "$ROOT/scripts/kokoro-install.sh" --uninstall
bash "$ROOT/scripts/kokoro-install.sh" --install
Model cache is preserved across uninstall, so reinstall reuses the cached model.
Troubleshooting
| Issue | Cause | Solution |
|---|---|---|
| Upgrade fails | No internet or PyPI down | Check connectivity, retry |
| Import error after | mlx-audio incompatibility | Clean reinstall: --uninstall then --install |
| Model download slow | Large download | Wait for HuggingFace download to complete |
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.
- 2d ago First seen · 81 lines · 32 tokens per session scan A 4161664e0f01
augment is a skill published in the GitHub repository terrylica/cc-skills (62 stars, last pushed today), licensed MIT. It adds 32 tokens to every session and 681 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 2026-09-05.
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