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Agent-skills index for multi-workflow products

If the product has several workflows, publish separate skill files plus a `/.well-known/agent-skills/index.json` manifest instead of forcing one giant capability blob.

rare tactic
Best-fit channelAI Search · Documentation · Integrations
Stage + contextagent enablement · developer experience · documentation · activation
BudgetFreebudget tier
Suggested operator signalShare of target users completing the product's first-value action

Why this can grow a startup

A complex product becomes easier to use when each workflow can describe itself cleanly. Separate skill files let an agent load only the relevant instructions, while a discovery index keeps the set organized. That usually produces cleaner tool use than one oversized capability file that tries to cover everything at once.

Source-backed example

Mintlify supports multiple skill files in a skills directory and exposes them through `/.well-known/skills/` and the recommended `/.well-known/agent-skills/index.json` discovery endpoint.

Source-reported evidence

Source: Mintlify Docs · Browse Mintlify Docs tactics

`GET /.well-known/agent-skills/index.json` returns a manifest of available skills

Attributed to the cited source; GrowthDex has not independently verified it. Use this as context, not as a forecast, benchmark, or recommended target.

Evidence scope: claims and metrics are attributed to the linked source; GrowthDex has not independently replicated the reported result. Check the original context and validate fit before applying it. Read the evidence methodology.

Source discovered: May 27, 2026

AI SearchDocumentationIntegrationsagent enablementdeveloper experiencedocumentationactivation
GrowthDex operator note

When to use it

Use this when AI Search, Documentation, Integrations is relevant to agent enablement, developer experience, documentation and you can run a bounded test with a free budget.

When not to use it

Do not use it as a substitute for customer evidence, a clear owner, or a measurable stop condition. Local platform rules and market behavior still need checking.

How to do it

  1. Choose one target segment and define the exact next action this tactic should prompt.
  2. Adapt the tactic to AI Search and Documentation, using evidence from Mintlify Docs as context—not as a promised result.
  3. Record a baseline for: Share of target users completing the product's first-value action. Set a guardrail that would make you pause the test.
  4. Run a narrow pilot and choose a test window that fits the normal decision or use cycle; do not scale before you have observed the full cycle.
  5. Compare the signal with its baseline. Scale only if the intended action improves without crossing the guardrail; otherwise revise one variable or stop and record what you learned.
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