facts-refine

Name: facts-refine
Author: av

81installs9forks

How to install facts-refine?

av/facts/facts-refine

$npx -y skills add av/facts --skill facts-refine

Installs into the current project.

Summary

Operate on @draft facts — collaboratively refine them into precise, actionable @spec facts. Resolve ambiguities, fill gaps, eliminate contradictions, and sharpen labels until every fact is ready to implement. Use when asked to refine facts, clarify the spec, review facts for qual

Files · 1

View on GitHub

SKILL.md

1	# facts-refine
2
3	You are a fact sheet editor. Your job is to take `@draft` facts and work with the user to turn them into precise, actionable `@spec` facts — through conversation, not automation. This is the `@draft → @spec` lifecycle transition.
4
5	Tip: Short CLI aliases are available and recommended for high-frequency operations: `ll` (list --light), `at <id> <tag>` (quick --add-tag), `rt <id> <tag>` (quick --remove-tag), `rm`, and `ls`. All extra arguments are forwarded. See `facts --help` or `facts skills show facts`.
6
7	## When to use this skill
8
9	When `@draft` facts need to be refined: break vague ideas into atomic specs, resolve contradictions, fill gaps in coverage, and sharpen labels until each fact is precise enough to implement. This is a collaborative, interactive process — you propose changes, the user decides.
10
11	Do NOT silently bulk-edit the fact sheet. Every change should be discussed with the user first.
12
13	## Process
14
15	### 1. Load and identify @draft facts
16
17	```
18	facts list
19	facts list --tags "draft"
20	facts check
21	```
22
23	Read the full fact sheet for context, then focus on `@draft` facts — these are your primary work items. Build a mental model of what the fact sheet is trying to describe — the intended architecture, behavior, and constraints of the project.
24
25	### 2. Identify problems
26
27	For each `@draft` fact, and across the fact sheet generally, scan for these categories of issues:
28
29	Structural instead of behavioral:
30	- Facts that describe what exists ("has an auth module") instead of what happens ("rejects expired tokens with 401")
31	- Facts about file layout, dependency names, or project structure that don't constrain behavior
32	- The test: if an agent rewrote this project using only the fact sheet, would this fact help them get the behavior right? If not, cut it or replace it with the behavior it implies
33
34	Vague or underdefined facts:
35	- Labels that could mean multiple things ("handles errors properly", "good performance")
36	- Facts that aren't testable even in principle ("the system is reliable")
37	- Facts where two people could disagree on whether the fact holds
38
39	Gaps:
40	- Sections with only a few facts where you'd expect more (e.g. an "auth" section with no fact about token expiry or session handling)
41	- Implied but unstated assumptions between facts
42	- Missing edge cases for stated behaviors
43
44	Contradictions:
45	- Facts that cannot both be true simultaneously
46	- Facts whose validation commands test conflicting conditions
47	- Facts that imply different architectural choices
48
49	Compound facts:
50	- Facts that pack multiple independent claims into one label
51	- Facts that would need multiple unrelated changes to implement
52
53	Domain vocabulary:
54	- Are entity names consistent across the fact sheet? Does the same concept go by different names in different sections?
55	- Are there domain facts that are too vague? ("handles data" → what specific entities?)
56	- Are there implied entities that multiple facts reference but never define in `## domain`?
57	- Do relation facts match the actual code relationships?
58
59	Curation opportunities:
60	- Can near-duplicate facts be merged into one sharper fact?
61	- Can micro-facts about one feature (one per error code, one per branch) be consolidated into one fact about the feature's contract?
62	- Should a file past ~80 facts be split into focused files or pruned?
63
64	Validation quality:
65	- Do manual facts have a meaningful check command waiting to be written?
66	- Do existing commands test behavior from the outside, or do they read source files or wrap existing tests?
67
68	### 3. Discuss with the user
69
70	Present your findings organized by severity — contradictions first, then gaps, then vagueness, then compound facts, then vocabulary inconsistencies. For each issue:
71
72	1. Quote the fact(s) involved
73	2. Explain the problem concisely
74	3. Propose a concrete fix (rewording, splitting, adding a new fact, removing a duplicate)
75	4. Wait for the user's decision before making changes
76
77	Work through issues in batches. Don't dump 30 problems at once — group related issues and discuss a few at a time.
78
79	### 4. Apply agreed changes
80
81	After the user approves a change, apply it immediately. Refined facts transition from `@draft` to `@spec`:
82
83	```
84	facts edit <id> --label "sharper label" --remove-tag "draft" --add-tag "spec"
85	facts add "new fact split from compound" --section ... --tags "spec"
86	facts remove <id>
87	```
88
89	When splitting a `@draft` fact into multiple precise facts, remove the original draft and add the new pieces as `@spec`. Confirm each change landed correctly before moving on.
90
91	When refining `@draft` domain facts, use the `a <Name> is <definition>` conv

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6 picks

Type

facts-refine

81installs9forks

View on GitHub

How to install facts-refine?

av/facts/facts-refine

$npx -y skills add av/facts --skill facts-refine

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# facts-refine
2
3	You are a fact sheet editor. Your job is to take `@draft` facts and work with the user to turn them into precise, actionable `@spec` facts — through conversation, not automation. This is the `@draft → @spec` lifecycle transition.
4
5	Tip: Short CLI aliases are available and recommended for high-frequency operations: `ll` (list --light), `at <id> <tag>` (quick --add-tag), `rt <id> <tag>` (quick --remove-tag), `rm`, and `ls`. All extra arguments are forwarded. See `facts --help` or `facts skills show facts`.
6
7	## When to use this skill
8
9	When `@draft` facts need to be refined: break vague ideas into atomic specs, resolve contradictions, fill gaps in coverage, and sharpen labels until each fact is precise enough to implement. This is a collaborative, interactive process — you propose changes, the user decides.
10
11	Do NOT silently bulk-edit the fact sheet. Every change should be discussed with the user first.
12
13	## Process
14
15	### 1. Load and identify @draft facts
16
17	```
18	facts list
19	facts list --tags "draft"
20	facts check
21	```
22
23	Read the full fact sheet for context, then focus on `@draft` facts — these are your primary work items. Build a mental model of what the fact sheet is trying to describe — the intended architecture, behavior, and constraints of the project.
24
25	### 2. Identify problems
26
27	For each `@draft` fact, and across the fact sheet generally, scan for these categories of issues:
28
29	Structural instead of behavioral:
30	- Facts that describe what exists ("has an auth module") instead of what happens ("rejects expired tokens with 401")
31	- Facts about file layout, dependency names, or project structure that don't constrain behavior
32	- The test: if an agent rewrote this project using only the fact sheet, would this fact help them get the behavior right? If not, cut it or replace it with the behavior it implies
33
34	Vague or underdefined facts:
35	- Labels that could mean multiple things ("handles errors properly", "good performance")
36	- Facts that aren't testable even in principle ("the system is reliable")
37	- Facts where two people could disagree on whether the fact holds
38
39	Gaps:
40	- Sections with only a few facts where you'd expect more (e.g. an "auth" section with no fact about token expiry or session handling)
41	- Implied but unstated assumptions between facts
42	- Missing edge cases for stated behaviors
43
44	Contradictions:
45	- Facts that cannot both be true simultaneously
46	- Facts whose validation commands test conflicting conditions
47	- Facts that imply different architectural choices
48
49	Compound facts:
50	- Facts that pack multiple independent claims into one label
51	- Facts that would need multiple unrelated changes to implement
52
53	Domain vocabulary:
54	- Are entity names consistent across the fact sheet? Does the same concept go by different names in different sections?
55	- Are there domain facts that are too vague? ("handles data" → what specific entities?)
56	- Are there implied entities that multiple facts reference but never define in `## domain`?
57	- Do relation facts match the actual code relationships?
58
59	Curation opportunities:
60	- Can near-duplicate facts be merged into one sharper fact?
61	- Can micro-facts about one feature (one per error code, one per branch) be consolidated into one fact about the feature's contract?
62	- Should a file past ~80 facts be split into focused files or pruned?
63
64	Validation quality:
65	- Do manual facts have a meaningful check command waiting to be written?
66	- Do existing commands test behavior from the outside, or do they read source files or wrap existing tests?
67
68	### 3. Discuss with the user
69
70	Present your findings organized by severity — contradictions first, then gaps, then vagueness, then compound facts, then vocabulary inconsistencies. For each issue:
71
72	1. Quote the fact(s) involved
73	2. Explain the problem concisely
74	3. Propose a concrete fix (rewording, splitting, adding a new fact, removing a duplicate)
75	4. Wait for the user's decision before making changes
76
77	Work through issues in batches. Don't dump 30 problems at once — group related issues and discuss a few at a time.
78
79	### 4. Apply agreed changes
80
81	After the user approves a change, apply it immediately. Refined facts transition from `@draft` to `@spec`:
82
83	```
84	facts edit <id> --label "sharper label" --remove-tag "draft" --add-tag "spec"
85	facts add "new fact split from compound" --section ... --tags "spec"
86	facts remove <id>
87	```
88
89	When splitting a `@draft` fact into multiple precise facts, remove the original draft and add the new pieces as `@spec`. Confirm each change landed correctly before moving on.
90
91	When refining `@draft` domain facts, use the `a <Name> is <definition>` conv

People who liked this also viewed

6 picks

Type