Knowledge centered service

Support

Use when a support answer should outlive the case: capture knowledge in the flow of solving, keep help articles findable and right, and coach reuse.

by AutoGPTNewUpdated 12d ago

Instructions

Instructions your experts follow when using this skill.

Use this when an answer should outlive the case. Capture knowledge in the flow of solving, keep articles findable and right, and coach reuse.

What you need

The solved case with its evidence, the knowledge-base (KB) home and article template from prefs, and the search terms the customer used.

Run the loops

Run the Solve Loop on every case: search early and search often with the customer's own words, use what you find or flag the gap, solve the case, then capture what was missing. Searching is creating: preserve the search phrases as the seed of the new article. Knowledge capture is part of the solve, not after-work.
Draft the article from the template: problem in the customer's words, environment or eligibility, steps verified against the case record, and the fix with its receipt — complete thoughts, not complete sentences. When improving an article, add to the issue statements; never rewrite, edit, or delete existing ones. If confident and licensed, fix it; otherwise flag it. Every step carries its source; a step you cannot verify is cut, never guessed. Never publish before the owner says yes.
Score article quality on reuse, not prose: findability (would the customer's words hit it), accuracy (steps match the record), and completeness (edge cases named). Reuse is review: link each article to the cases it solved. Retire or merge dupes; a stale article past review gets flagged to the KB owner, not silently edited.
Track the Solve Loop weekly: reuse rate, self-serve resolution, failed searches, and unresolved bot turns. The top failed search becomes the next article draft; the top reused article gets a freshness check.
Coach the team on capture: one quoted miss per rep per week (solved without searching, solved without capturing), with the fixed habit named. Log captures, flags, and publishes.
Run the Evolve Loop monthly with the KB owner: content-health review (a scored article sample, archive or merge, domain gaps), the New-vs-Known check, and root-cause feedback to product. The weekly loop keeps answers flowing; the monthly loop keeps the collection healthy.

Output

The staged article or fix, the quality score with evidence, the weekly Solve metrics and monthly Evolve review, and the coach note.

Fallbacks

No KB access means staged drafts in chat with the publish path named, not filed guesses. Never invent article URLs or review dates.

Triggers7

Phrases that help your experts find this skill.

write a KB articlecapture knowledge from a casehelp article qualitytop failed searchesKB reuse ratestale help articleknowledge base gap

More skills

Research

Product marketing context

by AutoGPTFrom coreyhaines31/marketingskills/skills/product-marketing

When the user wants to create or update their product marketing context document. Also use when the user mentions 'product context,' 'marketing context,' 'set up context,' 'positioning,' 'who is my target audience,' 'describe my product,' 'ICP,' 'ideal customer profile,' or wants to avoid repeating foundational information across marketing tasks. Use this at the start of any new project before using other marketing skills — it creates `.agents/product-marketing.md` that all other skills reference for product, audience, and positioning context.

1 installedView

Research

Competitor profiling

by AutoGPTFrom coreyhaines31/marketingskills/skills/competitor-profiling

When the user wants to research, profile, or analyze competitors from their URLs. Also use when the user mentions 'competitor profile,' 'competitor research,' 'competitor analysis,' 'profile this competitor,' 'analyze competitor,' 'competitive intelligence,' 'competitor deep dive,' 'who are my competitors,' 'competitor landscape,' 'competitor dossier,' 'competitive audit,' or 'research these competitors.' Input is a list of competitor URLs. Output is structured competitor profile markdown files. For creating comparison/alternative pages from profiles, see competitors. For sales-specific battle cards, see sales-enablement.

1 installedView

Research

Customer insight research

by AutoGPTFrom coreyhaines31/marketingskills/skills/customer-research

When the user wants to conduct, analyze, or synthesize customer research. Use when the user mentions "customer research," "ICP research," "talk to customers," "analyze transcripts," "customer interviews," "survey analysis," "support ticket analysis," "voice of customer," "VOC," "build personas," "customer personas," "jobs to be done," "JTBD," "what do customers say," "what are customers struggling with," "Reddit mining," "G2 reviews," "review mining," "digital watering holes," "community research," "forum research," "competitor reviews," "customer sentiment," "PMF survey," "product/market fit survey," "customer interview questions," "interview outreach," "Sales Safari," or "find out why customers churn/convert/buy." Use for analyzing existing research assets, mining online sources, AND running primary research (interviews and surveys). For writing copy informed by research, see copywriting. For acting on research to improve pages, see cro.

1 installedView