BF daily-100-methodology
日更100条方法论 v1.0 —— 帮老板做IP、帮员工省力气、帮个人创作者提效。 基于创始人公开方法论的研究整理而成，提炼出可复用的SOP体系。 三层架构：核心方法论(本文) → 按需加载reference → 用户专属方案。 核心策略：7大（高频轰炸、两线叙事、争议切入、矩阵思维、N+1创新、SABCD品牌承接、反向侵蚀风险）。 口播模板：5种（反共识型/故事悬念型/方法论型/产品展示型/日常随记型）。 触发词：「日更100条」「饱和攻击」「帮我做方案」「帮我起号」「帮我写口播」「争议选题」「员工矩阵」「数据复盘」「日更百条方法论」。 适用场景：老板/创始人IP打造、企业员工矩阵内容提效、个人创作者短视频起号与运营。 局限：偏向商业/科技/战略领域的内容创作，非官方授权，不适用于纯情感/娱乐类内容。高频发布需配合平台规则使用。 素材整理时间：2026年5月。 制作者：何老师商业AI落地
日更100条方法论 v1.0 —— 帮老板做IP、帮员工省力气、帮个人创作者提效。 基于创始人公开方法论的研究整理而成，提炼出可复用的SOP体系。 三层架构：核心方法论(本文) → 按需加载reference → 用户专属方案。…
As a process F 33/100 · Will not run — References files that are not bundled: references/用户方案_{姓名}.md
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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 · 0
✓ No critical or high findings
Files scanned: 15. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - warning
missing-refreference to a missing file: references/用户方案_{姓名}.md
Process rating: all ten parameters 33/100
- 0Tools and files. 1 referenced file(s) missing: references/用户方案_{姓名}.md
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 1 mutating operations with no state check
- 100Steps. 64 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2210 tokens
- low 10 top-level sections: this looks like several domains in one skill
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
- -236 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 400: enough signal without eating the budget
- +4Structure: 50 headings
- +3Step-by-step instructions: 64 items
- +4Has examples (9 code blocks)
- +4Reference files are cited in the instructions (11 of 11)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.