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Root skill.md for product capability discovery

Publish a root `/skill.md` that tells agents what your product can do, which inputs it needs, and which constraints matter instead of forcing them to infer capabilities from scattered docs.

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

Why this can grow a startup

Discovery is only half the job. After an agent finds the site, it still needs a clean picture of what actions are actually possible. A capability file reduces bad guesses, improves workflow accuracy, and makes the product easier to use from AI tools without stuffing the answer into one long marketing page.

Source-backed example

Mintlify hosts a root `skill.md` file that summarizes product capabilities, required inputs, workflows, integrations, and constraints for AI agents, and says generation or updates can take up to 24 hours.

Source-reported evidence

Source: Mintlify Docs · Browse Mintlify Docs tactics

Mintlify publishes a root `skill.md` capability file and regenerates it as docs change

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 SearchDocumentationWebsiteagent enablementactivationdocumentationbrand trust
GrowthDex operator note

When to use it

Use this when AI Search, Documentation, Website is relevant to agent enablement, activation, 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.
Next move

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