opportunities
Skill0 starsChanged 3 months agoMITView on GitHub
Suggest Summation workflows from recent local IDE chats and the live catalog. Use when the user asks what Summation can do for their work, wants workflow ideas, use cases, how you can help, opportunity scan, or after onboarding when they consent to a local chat scan.
2 other projects use a version of this.
Adopted by
Most recently taken up by
- ansvisor/ansvisortheir own version, first seen Nov 8, 2026
- ai-search-guru/getcito-worlds-first-open-source-aio-aeo-or-geo-tooltheir own version, first seen Nov 8, 2026
Other versions2 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 2
- ai-search-guru/getcito-worlds-first-open-source-aio-aeo-or-geo-tool★ 432same name
- ansvisor/ansvisor★ 233same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
The file
We split this skill into the rules it gives an agent
6 rules. About 0 are common, 5 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈5
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 20
If they decline → skip the scan.
- Distinctive: line 21
Never paste long chat excerpts.
- Distinctive: line 27
Run the bundled scanner (local only, no network).
- Distinctive: line 70
When they choose a number → run that skill.
- Distinctive: line 75
Prefer catalog-grounded next steps when MCP works.
- Very specific: line 78
If not signed in: still list opportunities.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Summation opportunities
Turn recent local IDE chats + what’s already in Summation into a short list of concrete next steps. Privacy first: scan stays on this machine unless the user later runs a normal Summation tool.
When to run
- User: “what can Summation do for me?”, “workflows”, “use cases”, “how can you help my work?”
- the
opportunitiesskill - Handoff from
startafter the data gate (only with consent)
Privacy (say this once, plainly)
I can scan recent local Claude Code / Codex sessions on this machine for themes (metrics, SQL, reports, CSVs, …). Nothing is uploaded. I only show short theme summaries, not full transcripts. OK?
- If they decline → skip the scan; still suggest from live catalog / docs if signed in.
- Never paste long chat excerpts. Never invent table names.
Flow
1. Local session scan (optional after consent)
Run the bundled scanner (local only, no network). Prefer the plugin root when the host sets it:
# Prefer the spec plugin root; fall back to Claude's name for the same path:
python3 "${PLUGIN_ROOT:-$CLAUDE_PLUGIN_ROOT}/skills/opportunities/scripts/scan_sessions.py" \
--days 14 --limit-sessions 20 --json \
--project-substr "$(basename "$(pwd)")"
# If neither variable is set: path relative to this skill’s scripts/ directory:
python3 skills/opportunities/scripts/scan_sessions.py --days 14 --limit-sessions 20 --jsonCaps are intentional. Prefer --json and turn themes into customer language yourself. If the scan fails or finds nothing, say so and continue with catalog-only ideas.
2. Live Summation context (if signed in)
MCP: whoami (signin if needed) → list_data_connections / list_connection_datasets / search_tables or the catalog skill as needed.
- Have named tables → ground each idea in real names.
- No data yet → opportunities that start with the
connectskill or import, not fake schemas.
3. Present 3–5 opportunities
Numbered list. Each item:
- Theme — one short phrase (from scan label or catalog).
- Why it fits — tie to a redacted sample or a real table (not a wall of chat).
- Next step — one skill/action:
query,report,validate,connect,catalog,schedule,start.
Map themes roughly:
| Scan theme | Prefer |
| Metrics / KPIs / “why did it move” | query (analyst / ask_analyst for narrative) or ranked SQL with ORDER BY |
| SQL / warehouse | catalog then query; connect if no source |
| CSV / files | import / connect then catalog |
| Board / status / narrative | report → offer validate |
| Recurring / every Monday | report then schedule |
| Data quality / pipelines | catalog + spot-check query |
| Connect / explore source | connect / start |
4. Act on their pick
When they choose a number → run that skill. Do not dump the whole menu again.
Rules
- Local scan only for host chat history — no cloud “conversation intelligence.”
- Prefer catalog-grounded next steps when MCP works.
- Product map for “is X supported?” still comes from
https://docs.summation.com/llms.txt(see../api/references/product.md). - Outcomes in user chat; no OpenAPI archaeology.
- If not signed in: still list opportunities; first step is often the
signinorstartskill.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

