support-thread
Skill0 starsChanged 3 months agoMITView on GitHub
Analyze a support/incident chat thread and emit a structured triage: problem, environment, what's been tried, current hypothesis, requester expectations, next step, owner, risks, sources. Also classifies any commitment-shaped statements (confirmed / proposed / internal / unclear). Triggers: "整理 support thread", "客服", "/support".
In this repository7 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- templates/CLAUDE.mdCLAUDE.md
- approve-proposalSkill
- ingest-sourceSkill
- meeting-notesSkill
- propose-memory-updateSkill
- read-memorySkill
The file
We split this skill into the rules it gives an agent
4 rules. About 0 are common, 3 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
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 78
After producing the structured triage, suggest (but don't auto-write):
- Distinctive: line 89
Don't invent customer environment details — say "未知"
- Very specific: line 90
Don't escalate a proposed to confirmed commitment without explicit owner OK
- Distinctive: line 91
Don't write to commitments.md inline — go through propose / commit flow
≈ “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
support-thread
Extract actionable structure from a support/incident thread, and separate what was actually promised from what merely sounded like a promise. "客戶" below reads as whoever reported the problem — an external customer, another team, or the owner themselves filing against their own infra.
Input
A chat thread from any enabled channel (pull with
mcp__discord__fetch_messages, or mcp__slack__fetch_messages when the
external Slack adapter is wired in).
Optionally the customer's prior message / ticket if linked.
Output template
支援案件:<one-line problem>
客戶:<name / org if known>
來源:<thread permalink>
問題描述:
- <what the customer reports — facts, no speculation>
客戶環境:
- 產品/版本:<X>
- 系統:<OS / browser / cluster>
- 規模:<users / data / load if relevant>
- (or: 未知)
已嘗試處理:
- <step 1, who did it, outcome>
- <step 2, ...>
目前判斷:
- <best current hypothesis + 信心強度>
客戶期待:
- <what would 'solved' look like from their POV>
- <timeline they expect>
下一步:
- <action> · owner:<@who> · 預計:<when>
風險:
- <risk: SLA / churn / commitment leakage / blast radius>
關聯:
- 相關 issue / PR / past support thread: <links>Commitment classification
For every statement aimed at the customer in this thread, classify into:
confirmed commitment— agreed deliverable, with date + owner. Should be reflected inmemory/commitments.md.proposed— suggestion not yet ratified by both sides. Don't write to commitments yet; flag for owner to follow up.internal-only— said inside the team thread, not yet relayed externally.unclear— ambiguous wording (e.g. "we'll look into it") that may be misread as a commitment. Surface to owner with the exact quote.
End the output with a 承諾辨識: section listing each classified statement.
When to write memory
After producing the structured triage, suggest (but don't auto-write):
memory/commitments.md— add anyconfirmed commitmentmemory/open_questions.md— add open questions raised by the customer that the team can't answer yetmemory/current_understanding.md— if this thread changes how we understand the product / behaviour
Owner uses approve-proposal flow (contributors) or directly commits (owner).
What NOT to do
- Don't invent customer environment details — say "未知"
- Don't escalate a
proposedtoconfirmed commitmentwithout explicit owner OK - Don't write to commitments.md inline — go through propose / commit flow
Does it work?
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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.

