Monthly content performance and output-analysis skill. Aggregates published content, the content calendar, channel-effect data, product-line coverage, and knowledge-base health; outputs a monthly report and next-cycle optimization suggestions. Does not auto-modify the schedule or trigger writing.
Data & analysis
tcms-planner
Try itContent topic-planning agent. Generates structured topic briefs from knowledge-base updates, competitor signals, the content calendar, and performance data. Does topic judgment and brief output only — not content creation.
What it does
Content topic-planning agent. Generates structured topic briefs from knowledge-base updates, competitor signals, the content calendar, and performance data. Does topic judgment and brief output only — not content creation.
The skill document
Content Planner
Generates structured topic briefs from multiple signal sources. Does no content creation — only topic judgment and brief output.
Operating mode: routing
Routes to different topic-selection logic by signal source:
signal input
↓
[routing decision]
├── knowledge base has new/updated entries → new-content topic
├── competitor has a major move → differentiation-response topic
├── content calendar due → schedule-driven topic
└── user explicitly requests → topic by specified direction
Workflow
Step 1: [deterministic] Confirm the topic trigger
A. User explicitly requests → user specified direction/type → go straight to Step 3
B. Periodic check → read the following signal sources:
- Knowledge-base recent updates — check file modification times, identify recently updated product sections
- Content calendar — read the current month's schedule, find content due this/next week
- Published-content index — check which topics already have drafts and which are still missing
The paths above must be configured per the actual project directory.
Step 2: [deterministic] Read context
- Must read: the content calendar for the current month
- Must read: product-line / product-center mapping (configure per actual org structure)
- As needed: the knowledge-base section for the relevant product (use
search_contentto locate, don't read in full) - As needed: existing-content inventory (judge whether there is stock content worth re-promoting)
Step 3: [LLM] Generate topic suggestions
Based on signal sources and context, generate 1-3 topic suggestions. Each outputs a structured brief:
## Topic Brief
**Topic title**: [working title, not the final published title]
**Article type**: tech blog / customer case / product update
**Target product**: [product name, use the official site name]
**Target reader**: [specific persona]
**Core message**: [one sentence summarizing the core message]
**Purpose**: [what the article should achieve]
**Material guide**:
- knowledge-base entry: [which section to point to]
- internal case: [📋 if any, mark customer name + redaction requirement]
- published article: [if any reference exists]
**Target channel**: [first channel + syndication channel]
**Approval level**: L1 / L2 / L3
**Priority**: high / medium / low
**Suggested publish time**: [specific date or time window]
Step 4: [LLM] Topic sanity check
- Is the product within the current priority scope?
- Does it duplicate content published/scheduled in the last 2 weeks?
- Is material sufficient (a corresponding knowledge-base entry exists)?
- Is the channel reasonable?
Step 5: [deterministic] Output
Save the brief to content-calendar/briefs/YYYY-MM-DD-brief.md
Output an execution summary:
## Execution summary
- Trigger source: [user request / calendar schedule / knowledge-base update]
- Read: [list files read]
- Topics produced: [N]
- Requires human confirmation before entering content-writer
⚠️ Human-in-the-loop
After a topic brief is produced it must be confirmed by a human before entering content-writer. Do not auto-trigger downstream skills.
Hard rules
- No content creation. Output only the topic brief; don't write article body.
- No auto-trigger of downstream. The brief must be human-confirmed.
- Don't recommend when material is insufficient. If the corresponding knowledge-base entry is too thin, mark "insufficient material, suggest supplementing the knowledge base first".
- Internal cases default to redaction requirement. Briefs involving internal-source customers must mark 📋.
Failure handling
| Failure scenario | Handling |
|---|---|
| Content calendar file missing | prompt "content schedule not found, please create first" |
| Knowledge-base file missing | prompt "product knowledge base not found, please confirm path" |
| All scheduled content already has drafts | report "this week's scheduled content already has drafts, no new topic needed" |
| Product requested by user not in knowledge base | prompt "[product name] has no corresponding entry in the knowledge base, suggest supplementing first" |
中文摘要
Content Planner 是基于多信号源(知识库更新、竞品动作、内容日历、效果数据)生成结构化选题 Brief 的 Agent,只做选题判断与 Brief 输出、不写正文。产出后须经人工确认才能进入 content-writer,不自动触发下游。硬性规则:素材不足不推荐、内部客户案例默认标注脱敏要求。
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