blog-discourse

Name: blog-discourse
Author: AgriciDaniel

1.2kinstalls251forks

How to install blog-discourse?

agricidaniel/claude-blog/blog-discourse

$npx -y skills add AgriciDaniel/claude-blog --skill blog-discourse

Installs into the current project.

Summary

Research what people are actually saying about a topic in the last 30 days across Reddit, X / Twitter, YouTube, Hacker News, dev.to, Medium, and other public discourse platforms. API-free; uses WebSearch with platform-targeted site operators plus recency filters. Produces DISCOUR

Files · 1

View on GitHub

SKILL.md

1	# Blog Discourse: Real Discourse Research, API-Free
2
3	`blog-discourse` is the recency + engagement lens that `blog-researcher` (authority-first) lacks. It asks: in the last 30 days, what are practitioners and customers actually saying about this topic on the public web?
4
5	Adapted from the methodology of `last30days-skill` (Matt Van Horn, MIT, https://github.com/mvanhorn/last30days-skill). The upstream uses platform APIs; this sub-skill uses WebSearch with platform-targeted site operators. No API keys required.
6
7	## Commands
8
9	\| Command \| Purpose \|
10	\|---\|---\|
11	\| `/blog discourse <topic>` \| Produce a discourse brief at project-root `DISCOURSE.md` \|
12	\| `/blog discourse <topic> --days 90` \| Widen the freshness window from 30 to 90 days \|
13	\| `/blog discourse <topic> --feed-into brief` \| Run the brief, then immediately invoke `/blog brief <topic>` with DISCOURSE.md auto-loaded \|
14	\| `/blog discourse <topic> --feed-into write` \| Run the brief, then invoke `/blog write <topic>` \|
15	\| `/blog discourse <topic> --feed-into strategy` \| Run the brief, then invoke `/blog strategy <topic>` \|
16	\| `/blog discourse <topic> --input results.json` \| Skip search; build the brief from a pre-gathered results file. The flag name matches `scripts/discourse_research.py --input` directly. \|
17
18	## Workflow
19
20	### Phase 0: Topic Pre-Flight (mandatory)
21
22	Before any search, run the four keyword-trap checks from `skills/blog/references/research-quality.md` (Class 1 demographic shopping, Class 2 numeric trap, Class 3 overly-literal phrase, Class 4 generic single-noun). If the topic matches a class:
23
24	1. Emit a single one-line note: `Pre-Flight: matched Class N. Action: <reframe or clarifying question>.`
25	2. If the action is a clarifying question, STOP and wait for the user.
26	3. If the action is a reframe, proceed with the reframed query and document the reframe in the brief.
27
28	Running discourse research on a trap topic wastes WebSearch calls and produces noise.
29
30	### Phase 1: Topic Decomposition (Step 0.55)
31
32	For named-entity topics, decompose into discrete searchable queries. Use the checklist from `research-quality.md`:
33
34	- [ ] Primary entity (official statements, vendor site)
35	- [ ] Counter-perspective (critics, competitors, contrarians)
36	- [ ] Practitioner discourse (subreddits, forums, dev.to, Medium)
37	- [ ] Tangential entities (founder, parent org, related products)
38	- [ ] Time anchor (last 30 or 90 days)
39
40	Emit the decomposition at the top of the eventual brief so reviewers can see the search plan.
41
42	### Phase 2: Platform-Targeted WebSearch
43
44	For each decomposed query, run WebSearch with platform-targeted site operators. Compose 4 to 8 searches total per topic. Use these operators (the agent picks the relevant subset for the topic class):
45
46	\| Platform \| Operator \| When to use \|
47	\|---\|---\|---\|
48	\| Reddit \| `site:reddit.com/r/<sub>` or `site:reddit.com` \| Always (when a relevant sub is known or discoverable) \|
49	\| Hacker News \| `site:news.ycombinator.com` \| Tech, dev tools, startup topics \|
50	\| X / Twitter \| `site:x.com` or `site:twitter.com` \| Public discourse, influencer takes \|
51	\| YouTube \| `site:youtube.com` \| Walkthroughs, reactions, demos \|
52	\| dev.to \| `site:dev.to` \| Developer practitioner content \|
53	\| Medium \| `site:medium.com` \| Long-form practitioner commentary \|
54	\| GitHub \| `site:github.com` (for issues / discussions) \| Open-source projects \|
55	\| StackOverflow \| `site:stackoverflow.com` \| Concrete how-to problems \|
56	\| Substack \| `site:substack.com` \| Newsletter-form essays \|
57
58	Always include a recency filter when the platform supports it (Google's `after:YYYY-MM-DD` and `before:YYYY-MM-DD`). For `--days 30`, set `after:` to today minus 30 days. For `--days 90`, today minus 90 days.
59
60	### Phase 3: Result Collection
61
62	For each WebSearch result, capture (into a temporary results JSON file the script can consume):
63
64	```json
65	{
66	"platform": "reddit",
67	"url": "https://reddit.com/r/xxx/comments/yyy",
68	"title": "Original post title as visible in SERP",
69	"snippet": "SERP snippet text",
70	"date": "YYYY-MM-DD or null",
71	"engagement_proxy": "upvote/comment

People who liked this also viewed

6 picks

Type

blog-discourse

1.2kinstalls251forks

View on GitHub

How to install blog-discourse?

agricidaniel/claude-blog/blog-discourse

$npx -y skills add AgriciDaniel/claude-blog --skill blog-discourse

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# Blog Discourse: Real Discourse Research, API-Free
2
3	`blog-discourse` is the recency + engagement lens that `blog-researcher` (authority-first) lacks. It asks: in the last 30 days, what are practitioners and customers actually saying about this topic on the public web?
4
5	Adapted from the methodology of `last30days-skill` (Matt Van Horn, MIT, https://github.com/mvanhorn/last30days-skill). The upstream uses platform APIs; this sub-skill uses WebSearch with platform-targeted site operators. No API keys required.
6
7	## Commands
8
9	\| Command \| Purpose \|
10	\|---\|---\|
11	\| `/blog discourse <topic>` \| Produce a discourse brief at project-root `DISCOURSE.md` \|
12	\| `/blog discourse <topic> --days 90` \| Widen the freshness window from 30 to 90 days \|
13	\| `/blog discourse <topic> --feed-into brief` \| Run the brief, then immediately invoke `/blog brief <topic>` with DISCOURSE.md auto-loaded \|
14	\| `/blog discourse <topic> --feed-into write` \| Run the brief, then invoke `/blog write <topic>` \|
15	\| `/blog discourse <topic> --feed-into strategy` \| Run the brief, then invoke `/blog strategy <topic>` \|
16	\| `/blog discourse <topic> --input results.json` \| Skip search; build the brief from a pre-gathered results file. The flag name matches `scripts/discourse_research.py --input` directly. \|
17
18	## Workflow
19
20	### Phase 0: Topic Pre-Flight (mandatory)
21
22	Before any search, run the four keyword-trap checks from `skills/blog/references/research-quality.md` (Class 1 demographic shopping, Class 2 numeric trap, Class 3 overly-literal phrase, Class 4 generic single-noun). If the topic matches a class:
23
24	1. Emit a single one-line note: `Pre-Flight: matched Class N. Action: <reframe or clarifying question>.`
25	2. If the action is a clarifying question, STOP and wait for the user.
26	3. If the action is a reframe, proceed with the reframed query and document the reframe in the brief.
27
28	Running discourse research on a trap topic wastes WebSearch calls and produces noise.
29
30	### Phase 1: Topic Decomposition (Step 0.55)
31
32	For named-entity topics, decompose into discrete searchable queries. Use the checklist from `research-quality.md`:
33
34	- [ ] Primary entity (official statements, vendor site)
35	- [ ] Counter-perspective (critics, competitors, contrarians)
36	- [ ] Practitioner discourse (subreddits, forums, dev.to, Medium)
37	- [ ] Tangential entities (founder, parent org, related products)
38	- [ ] Time anchor (last 30 or 90 days)
39
40	Emit the decomposition at the top of the eventual brief so reviewers can see the search plan.
41
42	### Phase 2: Platform-Targeted WebSearch
43
44	For each decomposed query, run WebSearch with platform-targeted site operators. Compose 4 to 8 searches total per topic. Use these operators (the agent picks the relevant subset for the topic class):
45
46	\| Platform \| Operator \| When to use \|
47	\|---\|---\|---\|
48	\| Reddit \| `site:reddit.com/r/<sub>` or `site:reddit.com` \| Always (when a relevant sub is known or discoverable) \|
49	\| Hacker News \| `site:news.ycombinator.com` \| Tech, dev tools, startup topics \|
50	\| X / Twitter \| `site:x.com` or `site:twitter.com` \| Public discourse, influencer takes \|
51	\| YouTube \| `site:youtube.com` \| Walkthroughs, reactions, demos \|
52	\| dev.to \| `site:dev.to` \| Developer practitioner content \|
53	\| Medium \| `site:medium.com` \| Long-form practitioner commentary \|
54	\| GitHub \| `site:github.com` (for issues / discussions) \| Open-source projects \|
55	\| StackOverflow \| `site:stackoverflow.com` \| Concrete how-to problems \|
56	\| Substack \| `site:substack.com` \| Newsletter-form essays \|
57
58	Always include a recency filter when the platform supports it (Google's `after:YYYY-MM-DD` and `before:YYYY-MM-DD`). For `--days 30`, set `after:` to today minus 30 days. For `--days 90`, today minus 90 days.
59
60	### Phase 3: Result Collection
61
62	For each WebSearch result, capture (into a temporary results JSON file the script can consume):
63
64	```json
65	{
66	"platform": "reddit",
67	"url": "https://reddit.com/r/xxx/comments/yyy",
68	"title": "Original post title as visible in SERP",
69	"snippet": "SERP snippet text",
70	"date": "YYYY-MM-DD or null",
71	"engagement_proxy": "upvote/comment

People who liked this also viewed

6 picks

Type