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Get Started Free →Rosetta self-help: explains capabilities and usage. DEPRECATED.
.claude/skills/griddynamics-self-help-flow/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 55% | 0% |
| case-14 | ✗→✓ | ▲ Improved | 268% | 0% |
| case-03 | ✗→✓ | ▲ Improved | 75% | 0% |
| case-04 | ✗→✓ | ▲ Improved | 123% | 0% |
| case-05 | ✗→✓ | ▲ Improved | 23% | 0% |
<self_help_flow>
<description_and_purpose>
Audience: developers and orchestrators exploring Rosetta-powered workspaces. Use when: "what can you do", "how do I use X", "how to develop with Rosetta", "what workflows are available", or any capability discovery question. Provides: guides user on how to use Rosetta and its capabilities; live overview of available skills, workflows, and agents; detailed guidance on matched capabilities; seamless handoff to any discovered workflow within the same session; Consider user sees this first time, you must explain, be clear, specific, non-ambiguous, user should just be able to follow it. REMIND USERS: use /help-flow instead of /self-help-flow. self-help-flow is deprecated.
</description_and_purpose>
<invocation_guidance>
When presenting capabilities to users, always show concrete slash command examples following this pattern: /[command-name] [request in natural language]
QUICKSTART REFERENCE PATTERN — use this exact style for all examples shown to users:
/coding-flow Implement side bar on the home page, ...
/coding-flow Identify and implement fix, ...
/coding-flow Improve unit tests coverage to 85% for ...
/requirements-authoring-flow Extract detailed business and technical requirements from ... using subagents.
/modernization-flow Perform modernization phase 1 to reuse library refsrc/... using subagents.
/research-flow Investigate OAuth 2.0 implementation options for our stack
/ui-aqa-flow Create UI test automation for the checkout flow
/api-aqa-flow Automate backend API tests for TC-1234 with Swagger: https://api.example.com/swagger.jsonHOW WORKFLOWS EXECUTE: Workflows are multi-phase pipelines. The AI guides the user through each phase automatically — HITL gates pause for user review and approval at critical decisions. Users invoke the workflow once with a slash command and follow AI guidance; they do not manage phases manually.
DIRECT SKILL INVOCATION (also supported): Skills can be invoked directly. Slash command = folder name of the skill. Naming rule: skills/[folder-name]/SKILL.md → /[folder-name] [request]
WHAT MAKES A VALID DIRECT SKILL EXAMPLE — a valid request must have all three:
WORKFLOWS ARE SELF-CONTAINED — they invoke skills internally: coding-flow handles all coding tasks and invokes debugging, testing, and other skills itself as needed. Similarly, every other workflow invokes its own skills internally. Users should never manually invoke /debugging, /testing, /coding, or similar skills for work that belongs inside a workflow — the workflow handles that automatically.
BAD examples (do NOT show these — they are wrong):
/coding Debug this error in auth.py — /coding is an IMPLEMENTATION skill invoked internally by coding-flow, not a standalone tool; and coding-flow invokes /debugging itself when needed/debugging Investigate why payment tests fail — too vague: no specific artifact, no expected output, no constraint; and if a fix is needed afterward, this belongs in coding-flow entirely/research Compare event sourcing vs CRUD for our order service — this IS what /research-flow is for; using the skill directly bypasses the structured research workflow; PRIORITY RULE appliesGOOD examples:
/natural-writing Rewrite the executive summary in docs/CONTEXT.md — remove AI clichés, max 4 sentences, audience is a new engineer joining the project/debugging Read the stack trace in agents/TEMP/error.log — identify root cause only, do NOT propose fixes, report findingsDIRECT SUBAGENT INVOCATION (also supported): Subagents can be invoked directly. Slash command = file name without .md. Naming rule: agents/[name].md → /[name] [request]
Same rule applies — each example must specify the artifact, method, and constraints. Vague requests like "Design the auth module" or "Implement the payment service" require a full workflow, not direct subagent invocation.
GOOD examples:
/architect Question me and initialize as a loop a project-brief.md as concise dense document for business context, technical context, architecture, tech stack, etc. No coding./reviewer Check current git changes, understand what was changed and why, validate against AC, find gaps or possible issues according to DoD/reviewer Validate implemented changes by actually running the code and using manual QA by AIPRIORITY RULE — WORKFLOWS ARE PREFERRED: When a workflow and a skill or subagent share a similar name or purpose, always recommend the WORKFLOW. Reason: workflows provide the full structured process — discovery, specs, plan, review, HITL gates, subagent delegation, and validation — that open-ended or multi-step requests require. Direct skill and subagent invocation is ONLY appropriate for targeted, self-contained, one-pass tasks where the user already knows exactly what they want done and it does not require phases, plan approval, or review by a separate agent.
</invocation_guidance>
<workflow_phases>
<prerequisites phase="0", applies="ALL">
load-project-context loaded and fully executed.<prerequisites phase="0", applies="ALL">
<list_capabilities phase="1" subagent="discoverer" role="KB catalog lister">
LIST workflowsLIST skills, then LIST skills/<name> for each.LIST agentsCapability Catalog: name, type (workflow/skill/agent), description — from frontmatter only.Capability Catalog.</list_capabilities>
<match_and_acquire phase="2" subagent="discoverer" role="Capability matcher">
Capability Catalog.READ FLOW <name>.md / READ SKILL <name> / READ SUBAGENT <name> per its type (e.g., READ FLOW coding-flow.md).Capability Catalog. Output: Matched Capabilities.</match_and_acquire>
<guide phase="3" subagent="discoverer" role="Capability guide">
Capability Catalog and Matched Capabilities into developer-friendly guidance at 101 level.<invocation_guidance> — show real examples using the QUICKSTART format.Capability Catalog + Matched Capabilities + user request. Output: guidance message.natural-writing for final user-facing output.reasoning, and any currently useful.</guide>
<handoff phase="4" optional="true" type="orchestrator">
READ FLOW <selected workflow>.md if not already loaded.</handoff>
</workflow_phases>
</self_help_flow>
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 15,172 | 10,735 | -29% | 1 | 1 | 0% | 2,412 | 3,748 | +55% | 0 | 0 | — |
case-14 | fail→pass | 4,582 | 4,530 | -1% | 1 | 1 | 0% | 717 | 2,637 | +268% | 0 | 0 | — |
case-02 | fail→fail | 19,519 | 4,102 | -79% | 1 | 1 | 0% | 2,767 | 2,199 | -21% | 0 | 0 | — |
case-03 | fail→pass | 15,488 | 15,405 | -1% | 1 | 1 | 0% | 2,385 | 4,168 | +75% | 0 | 0 | — |
case-04 | fail→pass | 10,403 | 8,505 | -18% | 1 | 1 | 0% | 1,511 | 3,372 | +123% | 0 | 0 | — |
case-05 | fail→pass | 15,304 | 6,865 | -55% | 1 | 1 | 0% | 2,390 | 2,928 | +23% | 0 | 0 | — |
case-06 | pass→pass | 8,594 | 5,673 | -34% | 1 | 1 | 0% | 1,295 | 2,746 | +112% | 0 | 0 | — |
case-07 | fail→pass | 8,475 | 6,905 | -19% | 1 | 1 | 0% | 1,211 | 2,893 | +139% | 0 | 0 | — |
case-08 | fail→pass | 13,315 | 6,343 | -52% | 1 | 1 | 0% | 2,072 | 2,955 | +43% | 0 | 0 | — |
case-09 | fail→pass | 10,907 | 5,405 | -50% | 1 | 1 | 0% | 1,587 | 2,631 | +66% | 0 | 0 | — |
case-10 | fail→pass | 18,916 | 5,460 | -71% | 1 | 1 | 0% | 3,065 | 2,764 | -10% | 0 | 0 | — |
case-11 | fail→pass | 9,559 | 10,676 | +12% | 1 | 1 | 0% | 1,453 | 3,501 | +141% | 0 | 0 | — |
case-12 | fail→pass | 14,338 | 34,428 | +140% | 1 | 1 | 0% | 2,194 | 3,066 | +40% | 0 | 0 | — |
case-13 | fail→pass | 11,200 | 5,872 | -48% | 1 | 1 | 0% | 1,778 | 2,842 | +60% | 0 | 0 | — |
case-15 | pass→pass | 17,876 | 10,481 | -41% | 1 | 1 | 0% | 2,688 | 3,547 | +32% | 0 | 0 | — |
case-16 | pass→pass | 6,947 | 2,179 | -69% | 1 | 1 | 0% | 948 | 2,174 | +129% | 0 | 0 | — |
case-17 | pass→pass | 10,468 | 2,260 | -78% | 1 | 1 | 0% | 1,639 | 2,269 | +38% | 0 | 0 | — |
case-18 | fail→pass | 7,427 | 3,171 | -57% | 1 | 1 | 0% | 1,126 | 2,327 | +107% | 0 | 0 | — |
case-19 | fail→pass | 13,454 | 6,372 | -53% | 1 | 1 | 0% | 1,921 | 2,885 | +50% | 0 | 0 | — |
case-20 | pass→fail | 14,887 | 6,907 | -54% | 1 | 1 | 0% | 2,802 | 3,101 | +11% | 0 | 0 | — |
case-21 | pass→fail | 20,073 | 12,478 | -38% | 1 | 1 | 0% | 3,335 | 3,867 | +16% | 0 | 0 | — |
case-22 | pass→pass | 7,443 | 9,339 | +25% | 1 | 1 | 0% | 1,506 | 3,893 | +158% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted, and 21 counted toward the lift figure. The other 1 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +55 percentage points is the difference between those two pass rates over the 21 comparable cases. 2 cases got worse with the skill loaded, and they are included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.