* feat(workflows): add 13 workflow templates across engineering, business, and productivity Engineering: - bug-triage: reproduce path → root cause → fix plan - api-design: resource model → endpoints → OpenAPI spec - incident-postmortem: timeline → RCA → full postmortem report - test-generation: code analysis → edge cases → full test suite - refactor-plan: smell analysis → prioritised opportunities → migration plan Business: - competitor-analysis: profiles → SWOT → strategy report - product-spec: problem definition → user stories → full PRD - market-research: landscape → segments → research report Productivity/Thinking: - meeting-summary: raw notes → structured summary → follow-up email - decision-matrix: criteria → weighted scoring → recommendation memo - learning-plan: gap analysis → roadmap → week-1 day-by-day plan - job-application: job analysis → tailored resume → cover letter → interview prep - blog-post: research → outline → draft → SEO optimisation Closes #1912 on librefang/librefang * fix(workflows): overhaul existing 9 templates - data-pipeline: redesigned — original 'extract from URL' step was broken (LLMs cannot fetch URLs); replaced with paste-data approach (profile → clean_transform → analyse) with analysis_goal parameter - translate-polish: added target_language and register parameters; added back-translation step for accuracy verification - weekly-report: added team/audience parameters, richer extraction step, added Metrics and Notes sections - content-pipeline: added audience/tone parameters, added outline step between research and writing - content-review: fix category 'content' → 'creation' - customer-support: fix category 'support' → 'business' * style(workflows): convert all prompt_template strings to TOML multiline syntax Replace \n escape sequences with real newlines using triple-quote multiline strings ("""...""") across all 22 workflow templates. No content changes — formatting only. * style(hands): replace \n escape in reddit writer format example with multiline code block
70 lines
2.1 KiB
TOML
70 lines
2.1 KiB
TOML
id = "content-review"
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name = "Content Review"
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description = "Multi-agent content review pipeline that drafts, reviews for quality and accuracy, then produces a final edited version incorporating feedback."
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category = "creation"
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tags = ["content", "review", "writing", "editing"]
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[i18n.zh]
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name = "内容审校"
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description = "多智能体内容审校流水线,先起草内容,再分别审查质量和准确性,最后综合反馈生成终稿。"
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[[parameters]]
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name = "topic"
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description = "The topic or subject to write about"
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param_type = "string"
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required = true
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[[parameters]]
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name = "tone"
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description = "Desired tone (formal, casual, technical, persuasive)"
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param_type = "string"
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required = false
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default = "formal"
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[[parameters]]
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name = "word_count"
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description = "Target word count for the content"
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param_type = "number"
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required = false
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default = 500
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[[steps]]
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name = "draft"
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prompt_template = "Write a {{tone}} article about {{topic}} with approximately {{word_count}} words. Include a clear introduction, well-structured body, and conclusion. Use concrete examples where appropriate."
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[[steps]]
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name = "review_quality"
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prompt_template = """
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Review the following draft for writing quality. Evaluate clarity, coherence, grammar, tone consistency (target: {{tone}}), and overall readability. Provide specific, actionable feedback with line-level suggestions.
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Draft:
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{{draft}}
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"""
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depends_on = ["draft"]
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[[steps]]
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name = "review_accuracy"
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prompt_template = """
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Review the following draft for factual accuracy and logical consistency. Flag any claims that appear unsupported, statistics that need citation, logical fallacies, or misleading statements. List each issue with a suggested correction.
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Draft:
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{{draft}}
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"""
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depends_on = ["draft"]
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[[steps]]
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name = "final_edit"
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prompt_template = """
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Produce a final edited version of the draft below, incorporating the quality and accuracy feedback. Preserve the original voice and intent while addressing all identified issues.
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Original draft:
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{{draft}}
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Quality feedback:
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{{review_quality}}
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Accuracy feedback:
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{{review_accuracy}}
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"""
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depends_on = ["review_quality", "review_accuracy"]
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