CF tiktok-api
A TikTok API alternative on fetcher.sh — pay-per-call in USDC via x402, or prepaid credits with a Bearer key, no login and no app review. Use when the user wants to search TikTok posts by keyword and sort by most-liked or most recent within a date range, look up a post by its share URL or ID, scrape a TikTok profile by @username, pull a user's posts, followers, or followings, fetch a hashtag's posts, pull posts using a specific sound/music track, get posts from a location, or read a post's comments and comment replies. Also covers TikTok trend tracking, hashtag monitoring, influencer discovery, competitor content analysis, and TikTok data pipelines without official TikTok API access or a scraping browser.
A TikTok API alternative on fetcher.sh — pay-per-call in USDC via x402, or prepaid credits with a Bearer key, no login and no app review. Use when the user…
As a process F 44/100 · Will not run — References files that are not bundled: ../fetcher/SKILL.md, ../../task-guides/tiktok-viral-post-search.md, ../../task-guides/tiktok-profile-and-followers.md
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".
If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.
How to improve
- The text references files that are not there: add them or drop the references.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 10
✓ No critical or high findings
Medium and low: 10
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medium Exfiltration
net-credential-usereferences/scenarios.md:23Credential used in a network call (verify the destination is the intended service)curl -H "Authorization: Bearer $FETCHER_API_KEY" \
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medium Exfiltration
net-credential-usereferences/scenarios.md:31Credential used in a network call (verify the destination is the intended service)curl -H "Authorization: Bearer $FETCHER_API_KEY" \
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medium Exfiltration
net-credential-usereferences/scenarios.md:41Credential used in a network call (verify the destination is the intended service)curl -H "Authorization: Bearer $FETCHER_API_KEY" \
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medium Exfiltration
net-credential-usereferences/scenarios.md:53Credential used in a network call (verify the destination is the intended service)curl -H "Authorization: Bearer $FETCHER_API_KEY" \
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medium Exfiltration
net-credential-useSKILL.md:70Credential used in a network call (verify the destination is the intended service)curl -H "Authorization: Bearer $FETCHER_API_KEY" \
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medium Exfiltration
net-credential-useSKILL.md:108Credential used in a network call (verify the destination is the intended service)curl -H "Authorization: Bearer $FETCHER_API_KEY" \
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medium Exfiltration
net-credential-useSKILL.md:118Credential used in a network call (verify the destination is the intended service)curl -H "Authorization: Bearer $FETCHER_API_KEY" \
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medium Exfiltration
net-credential-useSKILL.md:131Credential used in a network call (verify the destination is the intended service)curl -H "Authorization: Bearer $FETCHER_API_KEY" -G \
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medium Exfiltration
net-credential-useSKILL.md:135Credential used in a network call (verify the destination is the intended service)curl -H "Authorization: Bearer $FETCHER_API_KEY" \
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low Exfiltration
net-credential-usereferences/scenarios.md:14Credential used in a network call (verify the destination is the intended service) (quoted — discussed, not commanded)Swap the `curl -H "Authorization: Bearer $FETCHER_API_KEY"` prefix for a bare
quoted
Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
missing-refreference to a missing file: ../fetcher/SKILL.md - warning
missing-refreference to a missing file: ../../task-guides/tiktok-viral-post-search.md - warning
missing-refreference to a missing file: ../../task-guides/tiktok-profile-and-followers.md - warning
missing-refreference to a missing file: ../../commands/tiktok-search.md - note
frontmatter-keyunknown frontmatter key "keywords"
Process rating: all ten parameters 44/100
- 0Tools and files. 4 referenced file(s) missing: ../fetcher/SKILL.md, ../../task-guides/tiktok-viral-post-search.md, ../../task-guides/tiktok-profile-and-followers.md
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 2 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 70When it triggers. States when to use, but not when not to
- 100Steps. 13 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1800 tokens
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 714: enough signal without eating the budget
- +4Structure: 9 headings
- +3Step-by-step instructions: 13 items
- +4Has examples (9 code blocks)
- +4Reference files are cited in the instructions (4 of 4)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.