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Convert prompt to saill

Skill HorizonBrute/Standardized_AI_Looping_Language-SAILL/skills/convert-prompt-to-saill

Standardized AI Looping Language

Install
npx -y skills add HorizonBrute/Standardized_AI_Looping_Language-SAILL --skill convert-prompt-to-saill

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Convert a natural-language prompt into a SAILL agent-team flow — roles with model groups, control-flow flags (parallel/wait/Loop/if needed/if asked/ask user), boxes for sub-teams and nesting, and -context- for run-time values. Use when the user types /convert-prompt-to-saill, says "turn this into SAILL", "convert my prompt to SAILL", or "express this as an agent team / SAILL flow".

SKILL.md

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Skill: /convert-prompt-to-saill

Model preference: #midcost (per horizon_aios_model_prefs.md; overridable by a prompt directive).

Turn "here's my prompt" into its SAILL form — the standard, shareable agent-team notation (roles + model groups + flags + boxes + loops + -context-). The deliverable is the compact, portable representation behind a plain-English request, which the user can then run, save as a team, or share. Authoritative grammar: documentation/system/agent_teams.md (SAILL, §8) and the flag catalog $HORIZON_ETC/agent_team_flags.md.

When to invoke

/convert-prompt-to-saill <prompt>, or the user asks to turn a prompt into SAILL / express work as an agent team.

Step 1 — Load the vocabulary (do not invent flags)

1.1 Recognized flags: python $HORIZON_BIN/resolve_agent_teams.py --flags. 1.2 Existing teams (reuse one if it fits): python $HORIZON_BIN/resolve_agent_teams.py --json. Use only flags in the registry and #groups defined in horizon_aios_model_prefs.md.

Step 2 — Analyze the prompt

Decompose the prompt into a flow:

  1. Roles — the distinct units of work; for each, a short charter (what it does).
  2. Order — sequential vs concurrent; mark concurrency with parallel + a following wait.
  3. Iteration — "until it passes / retry" → a **Loop:** back to a named role, with a cap.
  4. Gates — "ask me / approve first" → ask user; "only if needed" → if needed; "only if I ask" → if asked.
  5. Sub-agents / nesting — group related roles in a box [ … ]; name it for an ephemeral sub-team Name[ … ]; nest as deep as the prompt implies.
  6. Context values — anything left to runtime (a scope, a pass condition, a cap) → -context- / -context-<name>.

Step 3 — Map to SAILL

3.1 If the prompt matches a shipped team (e.g. "investigate and fix X"), reuse it by name and add only the prompt's specifics (scope, flags) — do not reinvent.

3.2 Otherwise compose roles. Assign each a #group by the kind of work (mirror horizon_aios_model_prefs.md Task-Class Routing): security / architecture / review → #highcap; research / exploration → #investigate; mechanical / edits / summarizing → #lowcost; debugging / coding → #debug; otherwise → #midcost.

3.3 Apply the flags, boxes, loops, and -context- from Step 2. Prefer named loop targets and the most one-line-readable form that stays faithful.

Step 4 — Output

4.1 The SAILL block — either the agent_teams.md role format (### Name + numbered roles) or a one-line box expression, whichever is clearer for this flow.

4.2 A short gloss: map each role / flag back to the phrase in the prompt it came from.

4.3 Call out any -context- placeholders and what fills them at run time.

Step 5 — Offer next steps

Offer to save it as a reusable team (/agent-teams), run it ("send this team …"), or test it (/test-agent-teams <name>). Do NOT execute the work here — this skill only converts.

Notes for the executing agent

  1. Use ONLY flags from the registry and #groups from model-prefs — never invent vocabulary. If the prompt needs a new one, offer /agent-teams (add a flag) or /model-prefs (add a group).
  2. SAILL governs control flow; a role's work is charter prose (§1.2) — keep "run skill X" / "scope to Y" in the charter or as -context-, never as a flag.
  3. Keep the output terse and human-readable — the value of SAILL is a compact, shareable form.
  4. This converts only; it never runs the flow.

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