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 adbertram/cli-tools --skill tiktok-clipping-cligit clone --depth 1 https://github.com/adbertram/cli-toolsWrote 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/adbertram/cli-tools/tiktok-clipping-cli)<a href="https://agentmods.dev/skills/adbertram/cli-tools/tiktok-clipping-cli"><img src="https://agentmods.dev/badge/skills/adbertram/cli-tools/tiktok-clipping-cli/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/adbertram/cli-tools/tiktok-clipping-cli"><img src="https://agentmods.dev/badge/skills/adbertram/cli-tools/tiktok-clipping-cli.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 | $0.00096 | $0.01808 |
| Opus 5.5 | $0.00038 | $0.00723 |
| Sonnet 5.5 | $0.00019 | $0.00362 |
| Haiku 4.5 | $0.00010 | $0.00181 |
Grade A, and why
tiktok-clipping-cli 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 today.
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 — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
<project_overrides>
Before service operations, run ~/.agents/skills/skill-expert/scripts/load-skill-overrides.sh tiktok-clipping-cli. Apply printed instructions alongside this skill; nonzero means stop and report the broken override.
</project_overrides>
<quick_start>
The tiktok-clipping CLI follows this pattern:
tiktok-clipping <command-group> <action> [arguments] [options]
| Task | Command |
|---|---|
| Persist control state; running requires verified exact account and approved sources | tiktok-clipping control set <STATE> |
| Validate leased model JSON from stdin, then execute once through trusted adapters | tiktok-clipping jobs apply |
| Account native receipt from stdin, then recheck its original lease before acting | tiktok-clipping jobs apply-text |
| Validate a native image-review receipt and its exact durable lease | tiktok-clipping jobs apply-visual |
| Get one durable job, excluding its ownership credential | tiktok-clipping jobs get <JOB_ID> |
| Queue an allowlisted trusted source record from bounded JSON stdin | tiktok-clipping jobs ingest |
| List durable jobs, including explicit failed, blocked and ambiguous states | tiktok-clipping jobs list |
| Recover expired leases, reconcile uploads and maintain campaign submissions | tiktok-clipping jobs maintain |
| Claim one durable job or return an explicit paused/unconfigured/idle state | tiktok-clipping jobs prepare |
| Read back an ambiguous upload without repeating publication | tiktok-clipping jobs reconcile <JOB_ID> |
| Revalidate blocked work or an explicitly proven pre-publication visual/render failure | tiktok-clipping jobs retry <JOB_ID> |
| Request a bounded new proposal for a proven quiescent failed render | tiktok-clipping jobs retry <JOB_ID> --revise-render --reason "Measured cut timing rejection" |
| Revalidate blocked preproposal text work after its original native process ended | tiktok-clipping jobs retry-text <JOB_ID> |
| Run a ready job; coordinator alone owns retries and side-effect budgets | tiktok-clipping jobs run <JOB_ID> |
| Append a trusted timestamped metric snapshot from stdin; unknown values stay null | tiktok-clipping metrics record |
| Read every clip's state, publication and latest measured performance | tiktok-clipping activity list |
| Read actual campaign acceptance/rejection and observed earnings | tiktok-clipping rewards refresh <JOB_ID> |
| Submit one post to its verified campaign before its verified campaign-specific deadline | tiktok-clipping rewards submit <JOB_ID> |
| Inspect setup, control, account, durable budgets and strategy version | tiktok-clipping status get |
| Restore recorded baseline; models cannot change hard policy | tiktok-clipping strategy rollback |
| Read exact baseline/current pointer and proposal-digest snapshot | tiktok-clipping strategy baseline-state --config /absolute/config.json |
| Explicitly install configured future baseline using expected snapshot JSON on stdin | tiktok-clipping strategy install-baseline --reason "Intentional future style space" --config /absolute/config.json |
| </quick_start> |
<essential_principles>
MANDATORY: Verify the live command shape before executing ANY tiktok-clipping command.
Consult usage.json when the repo or installed package ships it. If usage.json is absent, use tiktok-clipping --help, the relevant subcommand --help, and README.md instead. Never guess at command syntax.
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.
- today First seen · 94 lines · 96 tokens per session scan A 1de15a21a214
tiktok-clipping-cli is a skill published in the GitHub repository adbertram/cli-tools (6 stars, last pushed today), licensed MIT. It adds 96 tokens to every session and 1,808 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-11-07.
tiktok-clipping-cli compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| tiktok-clipping-cliadbertram/cli-tools | Skill | 6 | today | MIT | A | 96 | Claude Code, Codex |
| opencli-autofixjackwener/OpenCLI | Skill | 31k | yesterday | Apache-2.0 | A | 61 | Claude Code |
| surfnicobailon/surf-cli | Skill | 684 | yesterday | MIT | A | 53 | Claude Code, Codex |
| rdc-cliBANANASJIM/rdc-cli | Skill | 193 | 14d ago | MIT | A | 82 | Claude Code, Codex |
| pixiv-cli-ciFlanChanXwO/pixiv-cli | Skill | 132 | yesterday | MIT | A | 61 | Codex |
| acrawl-mcpMingye-Lu/AgenticCrawler | Skill | 15 | yesterday | MIT | A | 200 | Claude Code, Codex |
| debug-hubrexleimo/aios | Skill | 62 | yesterday | MIT | B | 66 | Claude Code, Codex |