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 crevideo/crevideo-reach --skill mcp-playbookgit clone --depth 1 https://github.com/crevideo/crevideo-reachWrote 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/crevideo/crevideo-reach/mcp-playbook)<a href="https://agentmods.dev/skills/crevideo/crevideo-reach/mcp-playbook"><img src="https://agentmods.dev/badge/skills/crevideo/crevideo-reach/mcp-playbook/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/crevideo/crevideo-reach/mcp-playbook"><img src="https://agentmods.dev/badge/skills/crevideo/crevideo-reach/mcp-playbook.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00249 | $0.06644 |
| Opus 5 | $0.00125 | $0.03322 |
| Sonnet 5 | $0.00050 | $0.01329 |
| Haiku 4.5 | $0.00025 | $0.00664 |
Grade A, and why
mcp-playbook scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- **`references/debugging.md`** — the 3-layer (curl readback → wire capture → source read) debugging method, common error→cause table, Copy-flow template requirement, sample-approval radios, and the version-change histor 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.
Crevideo Reach MCP — Playbook
Output language: respond in the merchant's working language — Chinese for China-POP sellers (分级 / 真实抽成 / 触达阶梯 …), English for US sellers (tier / all-in take-rate / outreach waterfall …). Tool names stay identical in both.
The deep-reference layer for the crevideo-reach MCP server. The MCP itself ships a baseline tool-map + typical flow via SERVER_INSTRUCTIONS; this skill covers what that baseline can't — the create flow, non-obvious constraints, and how to debug when behavior diverges from the brands-app UI.
Source of truth: if anything here disagrees with the live tool list in the running session, the live tools win (this doc can lag the MCP version). Only call tools that actually exist in the session; never assume historical or future tools.
When NOT to use
- Pure MCP-protocol or Claude-skill mechanics questions → wrong skill.
- Nothing about automations, creators, affiliate analytics, TikTok Shop, or the reach area → don't invoke.
Scope: affiliate (分销) + TikTok Shop product listing
The MCP exposes affiliate/distribution features plus TikTok Shop product onboarding. Campaign/marketing surfaces (campaign management, /report/* campaign reports, creator marketplace discovery, custom products, brand sampling) are not tools here — say they're out of scope. query_*_performance covers collaboration / affiliate-product / shoppable-video (affiliate), not campaign reports.
There is no natural-language→filter and no copy-polish endpoint — you (the LLM) translate the user's words into structured filters yourself, and you write/edit message copy yourself.
Tool map (89 tools, 16 groups)
Many tools fold multiple endpoints behind a view / action / scope / op_type param — pass those to drill in; don't expect one tool per endpoint.
- Automations (💳 on create):
list_automations,get_automation_detail,get_automation_task_results,preview_target_collab(free, 10-min token),create_target_collab,create_dm_automation,create_tc_dm_automation,clone_and_modify_automation,start_automation/pause_automation/delete_automation,update_dm_automation_text,create_bulk_tc_operation,manage_message_templates,get_dm_task_message_template. - TC direct entity (no automation wrapper):
list_target_collaborations,get_target_collaboration_detail,preview_target_collab_direct,create_target_collab_direct,update_target_collab_direct,cancel_target_collaboration,add_creator_to_target_collaboration. See "TC: two creation paths" below. - Open Collaboration (OC):
list_open_collaborations,get_open_collaboration_detail,create_open_collaboration,modify_open_collaboration,remove_open_collaboration,manage_open_collaboration_settings(get/edit),manage_open_collaboration_sample_rule(get/edit),remove_creator_from_open_collaboration,list_not_added_open_collaboration_products,get_open_collaboration_product_count,get_open_collaboration_status_counts. - Reporting (read-only, 3 tools):
query_collaboration_performance(scope: target/open/both),query_product_performance,query_shoppable_video_performance. Product/video breakdown/detail views run on TT-official REAL-TIME data (matches the brand-app page; video adds GPM + daily avg customers, product AOV is derived GMV÷orders); overview/trend stay on legacy aggregates — small drift between the two is expected, explain it rather than "fix" it. Breakdown lists use cursor pagination: pass each returnednext_page_tokenback unchanged aspage_token; the legacypagenumber does not advance them. There is NOquery_ai_insighttool — produce insight yourself by reading these three reports. - Affiliate orders:
list_affiliate_orders(TC dimension — the canonical "我分销卖了多少" answer;target_collaboration_idREQUIRED),list_customer_creator_orders(🚨 naming trap — CA dimension, NOT distribution GMV). - Creators:
list_affiliate_creators,get_creator_detail,manage_creator_blacklist(list/add/remove/modify),update_creator_metadata,manage_segment,manage_journey,manage_creator_lists,get_creator_list_overview,search_affiliate_creators(filters orcreator_keywordto resolve a @handle → user_id),find_similar_creators,recommend_creators(达人罗盘 — backend match-score recommendation by product),list_customer_advocates,manage_customer_advocates(6 actions — collect/collect_history/set_notes/get_detail/list_records/get_overview; no add_tag),manage_contact_enrichment(add_creators is a source switch: manual/filter/list/segment/journey/target_collab). - Content:
list_affiliate_content(TT-official REAL-TIME published videos — needsshop_cipher, optional date range/account_type/page_token; pass returnednext_page_tokenback aspage_tokento continue),get_affiliate_content_products,manage_affiliate_content(list/add_notes — legacy row ids; use its ids for notes, not the real-time list's). - DM conversations:
list_conversations,get_conversation_messages(cursor-paginated, default 20 per page),send_message(real outbound —text,image,text_image_card, ortext_products_card; by conversation_id OR unique_id='@handle' which auto-finds/opens the thread; all modes require confirm),search_conversations,create_conversation,list_conversation_groups,list_group_conversations,manage_conversation_groups. - Email (10 tools, LIVE):
list_email_conversations,get_email_detail,send_email,reply_email,manage_email_templates(CRUD),manage_email_drafts(CRUD),mark_email_as_read,move_emails_to_trash,manage_email_groups(folders — list/create/rename/delete/add/move/remove),manage_email_trash(list/restore/delete_permanently).send_email/reply_emailare real outbound — confirm intent first. - Samples (申样):
manage_sample_auto_approval(get/update rules),manage_sample_applications(list/approve/reject the manual queue). - Shop/catalog reads:
list_shops,list_products,get_product_detail,list_creator_categories. - Product listing (currently US-only, 10 tools):
check_product_listing_prerequisites,discover_product_category,get_product_category_requirements,search_product_brands,get_product_fulfillment_options,search_product_compliance_entities,upload_product_asset,check_product_listing,create_product_listing,get_product_listing_detail.
What ships with it
3 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.
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 Changed · +23 lines d690817134da
- 3d ago Changed · +45 lines · +30 tokens per session b0d31cbf486a
- 8d ago Changed · +5 lines f188a5416a08
- 12d ago First seen · 134 lines · 219 tokens per session scan A 8576af678859
mcp-playbook is a skill published in the GitHub repository crevideo/crevideo-reach (7 stars, last pushed yesterday), licensed MIT. It adds 249 tokens to every session and 6,644 once invoked, about $0.0012 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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