9k tokens
context cost
the whole folder, loaded on every use
34
files
ships runnable scripts
0
copies elsewhere
how many repositories repackaged it
144
stars on the repo
on the repository, not the skill itself
Install
one command, takes just this skill from the repository
npx skills add https://github.com/naodeng/awesome-qa-skills --skill requirements-analysisCopy
What comes with it
34 974 bytes besides the instruction
README.md
agents/openai.yaml
evals/cases/basic-success.yaml
evals/cases/edge-incomplete-input.yaml
evals/cases/edge-risk-priority.yaml
evals/eval.yaml
output-formats.md
output-templates/template-csv.csv
output-templates/template-excel.tsv
output-templates/template-json.json
output-templates/template-markdown.md
output-templates/template-word.md
output-templates/template-xmind.md
prompts/requirements-analysis.md
references/local/FAQ.md
references/troubleshooting.md
scripts/batch_convert_templates.py
scripts/convert_formats.py
scripts/convert_output_formats.py
scripts/convert_to_csv.py
scripts/convert_to_excel.py
scripts/convert_to_json.py
scripts/convert_to_markdown.py
scripts/convert_to_word.py
scripts/convert_to_xmind.py
scripts/parse_csv.py
scripts/parse_excel.py
scripts/parse_formats.py
scripts/parse_json.py
scripts/parse_markdown.py
scripts/parse_output_formats.py
scripts/parse_word.py
scripts/parse_xmind.py
The instruction itself
7 sections, as written by the author
Requirements Analysis (English)
中文版： See the corresponding Chinese skill.
When to Use
Need help with requirements analysis in a real project context.
Need an output that can be used directly for execution, review, or follow-up.
Workflow
Read and follow the main prompt listed under Progressive disclosure (coverage, structure, quality bar).
Add only project context that changes the result: scope, environment, constraints, risks, dependencies, expected deliverable.
If input is incomplete, return a usable first draft and explicitly mark assumptions and gaps.
Default to Markdown; switch formats only when the user asks.
Core Constraints
Prioritize by risk / business impact — do not treat everything equally.
Separate confirmed facts from current assumptions.
Do not invent endpoints, fields, environments, or root causes the user did not provide.
Keep output executable: concrete scenarios, clear priority, clear next steps.
Progressive Disclosure
Before producing output, read and follow prompts/requirements-analysis.md (minimum coverage, output structure, quality bar).
When Excel/CSV/JSON/Word is requested: read output-formats.md and honor the format.
When a ready-made template fits: use matching files under output-templates/.
For deep framework/troubleshoot/schema notes: read only the relevant file(s) under references/, do not load the whole directory.
For format conversion or helper checks: prefer existing scripts/ over reinventing.
For evaluating/regressing this skill: use evals/ with skill-up.
Pre-delivery Checklist
[ ] Followed the main prompt's output structure
[ ] Minimum coverage focus: scope summary, business objective, clear and unclear requirements, missing rules, edge or exception conditions, testability gaps, dependencies and impacts, risk priority, ... (details in main prompt)
[ ] Covered the minimum checklist, or explained omissions
[ ] High-risk items have explicit priority
[ ] Did not invent details the user did not provide
[ ] Assumptions and gaps are marked
Common Pitfalls
Do not pretend completeness when scope/context is missing.
Do not treat every item as equally important.
Do not skip assumptions and information gaps.
Do not dump generic theory unrelated to the current toolchain.