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 sergeyizmailov/knowledge-delta-skills --skill tiktok-adsgit clone --depth 1 https://github.com/sergeyizmailov/knowledge-delta-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/sergeyizmailov/knowledge-delta-skills/tiktok-ads)<a href="https://agentmods.dev/skills/sergeyizmailov/knowledge-delta-skills/tiktok-ads"><img src="https://agentmods.dev/badge/skills/sergeyizmailov/knowledge-delta-skills/tiktok-ads/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/sergeyizmailov/knowledge-delta-skills/tiktok-ads"><img src="https://agentmods.dev/badge/skills/sergeyizmailov/knowledge-delta-skills/tiktok-ads.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 | $0.00064 | $0.02029 |
| Opus 5.5 | $0.00026 | $0.00812 |
| Sonnet 5.5 | $0.00013 | $0.00406 |
| Haiku 4.5 | $0.00006 | $0.00203 |
Grade A, and why
tiktok-ads 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 1mo 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 — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.
TikTok Ads
Reviewed 2026-09-14 against TikTok's full official documentation plus RU/EN practitioner
sources. UI, eligibility, policy, pricing and benchmarks are volatile — verify the current primary
source when the answer depends on current behaviour (00).
Operate as a senior practitioner who has not worked this account before: derive, do not assume.
This skill ships no default strategy — on purpose
The three inputs that decide structure — the payout event, the conversion volume the account can feed, and the GEO's policy and auction — vary more than the platform does. Anything shaped like a universal launch template is an artefact of one GEO and one vertical.
Read references/01-research-protocol.md before proposing anything. It owns the intake, the
constraints gate, the bounded research pass, and the derivation. The rest of this skill is the
material that protocol draws on.
Diagnosing an existing account rather than planning a new one? Go straight to 09 (diagnosis order)
and the reference the symptom names — but come back to 01 § H before you change the strategy,
because "which input was wrong" is a derivation question, not a reporting one.
intake → constraints gate → bounded research → derive → pre-mortem → plan → execute → review
Guardrails — these fire before any reference is read
- TikTok's
operation_statusdefaults toENABLE. An object created without it is live and spending. Opposite of Meta. bid_typehas exactly two values —BID_TYPE_NO_BID(Maximum Delivery) andBID_TYPE_CUSTOM(Cost Cap). Meta's bid vocabulary does not exist. Value/ROAS bidding is a separate axis (deep_bid_type) and cannot be combined with Cost Cap.- TikTok publishes two learning numbers and they disagree — "~25 results or 7 days" before
volatility falls, and "7 days to reach 50 conversions" for an underperforming ad group. Use 25
to decide when a number is readable and 50 to decide whether a structure can be fed (
05). Porting Meta's hard 50-conversion exit gate makes you over-consolidate and mis-time every verdict. - The "±20% budget change resets learning" rule appears in no TikTok document. The one documented budget rule is that an update must be ≥105% of current spend.
- There are no location exclusions. You positively select. Rewrite any exclusion-based plan.
- Attribution window locks at ad-group creation and is not a reporting parameter. Two windows means two ad groups, decided up front.
- Currency, timezone and country are permanent at ad-account creation, and budget minimums are
base × per-currency ratio. A USD template on a JPY (×100) or IDR (×10,000) account is wrong by orders of magnitude, upward. - There is no
SALESobjective enum (it isWEB_CONVERSIONS/PRODUCT_SALES+virtual_objective_type), no Store Traffic objective, and Collection Ads can no longer be created. - Tracking fails silently. Hash mismatches,
event_idmismatches and droppedttclidthrow no error anywhere. Fire one real test conversion and watch it arrive before launching. - A rejected ad cannot be enabled into life — build a new one. And an appeal re-reviews the whole ad group, with one appeal allowed.
What ships with it
18 files 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.
- playbooks/app-promotion.md 4.0 KB
- playbooks/ecommerce.md 3.7 KB
- playbooks/finance-investment.md 4.8 KB
- playbooks/igaming-casino.md 14 KB
- playbooks/lead-gen.md 3.8 KB
- playbooks/README.md 1.5 KB
- references/00-evidence-and-maintenance.md 8.2 KB
- references/01-research-protocol.md 14 KB
- references/02-account-model-and-access.md 12 KB
- references/03-objectives-and-structure.md 10 KB
- references/04-targeting-and-audiences.md 8.1 KB
- references/05-bidding-budgets-delivery.md 12 KB
- references/06-creatives-identity-spark.md 12 KB
- references/07-tracking-pixel-events-api.md 17 KB
- references/08-policy-verticals-geo.md 12 KB
- references/09-diagnostics-and-optimization.md 8.8 KB
- references/10-ecommerce-catalog-shop.md 6.4 KB
- references/11-practitioner-field-notes.md 11 KB
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.
- 1mo ago First seen · 145 lines · 64 tokens per session scan A b62705344946
tiktok-ads is a skill published in the GitHub repository sergeyizmailov/knowledge-delta-skills (3 stars, last pushed 1mo ago), licensed MIT. It adds 64 tokens to every session and 2,029 once invoked, about $0.0003 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 2026-09-15.
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