agentleFS
Sign inStart free
Anuj7411Anuj7411/sipcode/skills/estimate/SKILL.md

estimate

Skill46 starsChanged 31 days agoMITView on GitHub

Predict the dollar cost of a coding task across Opus 4.7, Sonnet 4.6, and Haiku 4.5 BEFORE the user runs it. Pure heuristic + historical-anchor math, zero LLM calls. Use when the user asks "how much will X cost?", "is this task worth doing on Opus?", "estimate the refactor", or any pre-flight pricing question.

28 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use team-audio, playtest-report and 10 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • CoralGameSkill

    team-audio

    Orchestrate audio team: audio-director + sound-designer + technical-artist + gameplay-programmer for full audio pipeline from direction to implementation.

    Also in 13 projects that use this

  • CoralGameSkill

    playtest-report

    Generates a structured playtest report template or analyzes existing playtest notes into a structured format. Use this to standardize playtest feedback collection and analysis.

    Also in 12 projects that use this

  • lilangMaxSkill

    asset-spec

    Generate per-asset visual specifications and AI generation prompts from GDDs, level docs, or character profiles. Produces structured spec files and updates the master asset manifest. Run after art bible and GDD/level design are approved, before production begins.

    Also in 10 projects that use this

  • lilangMaxSkill

    create-control-manifest

    After architecture is complete, produces a flat actionable rules sheet for programmers — what you must do, what you must never do, per system and per layer. Extracted from all Accepted ADRs, technical preferences, and engine reference docs. More immediately actionable than ADRs (which explain why).

    Also in 10 projects that use this

  • +3 more from CoralGame
  • +5 more from lilangMax

The file

We split this skill into the rules it gives an agent

2 rules. 0 are common, 1 is distinctive, and 1 is very specific to this project.

  • 0

    Common

    Most of the 25 edited versions we read keep these.

  • 1

    Distinctive

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Call the sipcode:estimate_task_cost MCP tool with:

    line 7
  2. Distinctive:

    Never invent precision. Round to whole cents unless the estimate is sub-$0.10.

    line 17

“Common” is measured: kept by at least 6 in 10 of the 25 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Sipcode — Estimate (pre-flight cost prediction)

Call the sipcode:estimate_task_cost MCP tool with:

  • task: natural-language task description (≥3 chars). Example: "refactor the auth pipeline across 6 files".
  • cwd: absolute path to the project root the task will run in. If the user didn't specify a directory, ask before calling.

The tool returns per-model dollar predictions with a confidence band.

When presenting:

  • Show all three models (Opus / Sonnet / Haiku) side-by-side, not just the most expensive.
  • Surface the confidence band — if it's wide, say so honestly. If the tool reports confidence: "low" because no past sessions matched this complexity tier, mention that the estimate is heuristic-only.
  • Make a model recommendation grounded in the cost spread. If Haiku is within ~10% of Sonnet for the task, recommend Haiku. If the task complexity is high (5+ files), Opus is usually worth the cost.
  • Never invent precision. Round to whole cents unless the estimate is sub-$0.10.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

Reviews can't be read right now.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

Check your setup, free