SigmaLifting CLI

v0.1.0

Use when the user wants to create, translate, import, validate, inspect, or update powerlifting training programs or workout logs for SigmaLifting using sigm...

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Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for sigmalifting-dev/sigmalifting-cli.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "SigmaLifting CLI" (sigmalifting-dev/sigmalifting-cli) from ClawHub.
Skill page: https://clawhub.ai/sigmalifting-dev/sigmalifting-cli
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install sigmalifting-cli

ClawHub CLI

Package manager switcher

npx clawhub@latest install sigmalifting-cli
Security Scan
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Benign
high confidence
Purpose & Capability
The name/description match the instructions: the skill is a modeling guide that expects an installed sigmalifting-cli executable and tells the agent how to use it. However, the registry metadata lists no required binaries even though the SKILL.md and README clearly assume the presence of the sigmalifting-cli executable.
Instruction Scope
SKILL.md confines agent activity to reading program/process bundles, running sigmalifting-cli commands, validating/normalizing JSON, and avoiding direct JSON edits. It does not ask the agent to exfiltrate data or call external endpoints beyond invoking the local CLI. This scope is consistent with the stated purpose.
Install Mechanism
There is no formal install spec in the registry (instruction-only), which is low-risk. README suggests installing the CLI via 'npm install -g https://github.com/sigmalifting/cli.git' — a user-supplied GitHub URL. That is a normal way to obtain a CLI but the skill doesn't declare or enforce it; verifying the upstream repo/release before installing is recommended.
Credentials
The skill declares no required environment variables, which is reasonable. SKILL.md references SIGMALIFTING_HOME/--store-root as a way to control the local JSON store but does not declare SIGMALIFTING_HOME in registry metadata. This is a minor mismatch (an optional env var is referenced but not documented).
Persistence & Privilege
always:false and default agent invocation settings are appropriate. The skill does not request persistent/system-wide privileges or modifications to other skills or system configs.
Assessment
This skill is an instruction-only guide for using a local sigmalifting-cli; it does not itself install code or ask for secrets. Before installing/using: 1) Confirm you actually want to install the external 'sigmalifting-cli' tool and inspect the upstream GitHub repo or official release (README suggests installing from https://github.com/sigmalifting/cli.git). Prefer pinned releases and check commit history or release artifacts. 2) Be aware the skill expects a local store (SIGMALIFTING_HOME or --store-root) — set that to a project or test directory you control; do not point it at sensitive system paths. 3) Ask the publisher to add a formal install spec or declare the required binary in metadata so the platform can verify availability before invocation. 4) Run the CLI commands in an isolated/test environment first to confirm behavior (doctor, help, schema, validate) before allowing the agent to mutate real program/process stores. 5) If you need higher assurance, inspect the CLI code or request signed releases/sha256 checksums from the maintainer.

Like a lobster shell, security has layers — review code before you run it.

clivk97feckzyet6chzwmz7cywahbn85qvjwlatestvk97feckzyet6chzwmz7cywahbn85qvjwpowerliftingvk97feckzyet6chzwmz7cywahbn85qvjwsigmaliftingvk97feckzyet6chzwmz7cywahbn85qvjwstrength trainingvk97feckzyet6chzwmz7cywahbn85qvjw
20downloads
0stars
1versions
Updated 11h ago
v0.1.0
MIT-0

SigmaLifting CLI

Use this skill when working with SigmaLifting CLI bundles, especially when turning a spreadsheet, manual, or public program into a program-import bundle.

Core Boundaries

  • Treat the CLI as a standalone JSON tool.
  • Use the installed sigmalifting-cli executable as the contract and validation engine.
  • Do not rely on Realm, Expo file APIs, or app services for CLI behavior.
  • Stored program changes may cascade into linked process bundles in the CLI JSON store; file-only bundle edits cannot update unrelated files unless the command output is saved to the store.
  • Prefer contract-valid JSON bundles over app-coupled shortcuts.
  • Treat this skill folder as the modeling guide, not as the executable schema.

Agent Mutation Policy

SigmaLifting JSON is the CLI's internal storage and import/export contract. It is not an agent editing surface.

Agents must not directly create or mutate program/process bundle JSON with file edits, apply_patch, ad hoc scripts, jq, editor operations, or manual rewrites of files in the CLI store. Reading JSON for diagnosis is allowed; writing JSON directly is not.

All bundle creation and mutation must go through CLI commands:

  • create initial bundles with template, program create, process create-from-program, or xlsx import
  • change programs with program add-block, program update-block, program add-day, program update-schedule, program add-exercise, program update-exercise, custom-lift commands, and the exercise-progression intent commands such as program set-anchor, program add-set-group, program set-week-value, and program toggle-backoff
  • change processes with process update-* commands and narrow intent commands such as process set-one-rm
  • write command results with --out or let the local store persist command output
  • import externally supplied JSON only through validate; use normalize only when the user explicitly wants CLI cleanup/repair

validate is a strict import/acceptance gate for existing JSON. If it fails with repair warnings, use normalize to produce the cleaned bundle before inspecting or importing it.

If the CLI does not expose a command for a needed mutation, stop and report the CLI command gap or add the command first. Do not bypass the CLI by patching raw JSON.

CLI Discovery

When the installed CLI and this skill are available, inspect the tool before modeling:

  1. run sigmalifting-cli doctor --compact
  2. read this SKILL.md and any task-relevant files in references/
  3. run sigmalifting-cli help --compact
  4. run sigmalifting-cli schema list --compact
  5. run sigmalifting-cli template program-import --compact or template process-import --compact

Program and process bundle results persist as local JSON by default. Use sigmalifting-cli store path to locate the store, and use SIGMALIFTING_HOME or --store-root when you need an explicit test or project-local store.

Schema Contract

Do not treat this skill file as the schema.

This skill explains modeling judgment: block boundaries, weekly structure, set-group semantics, and common translation mistakes. The installed CLI is the schema source of truth.

Schema mentions in this skill are routing instructions, not schema documentation. They tell the agent which CLI commands to call before building CLI payloads or accepting imported JSON.

Before building CLI command payloads or importing existing JSON, get the executable contract from the CLI:

  1. sigmalifting-cli schema list --compact
  2. sigmalifting-cli schema show <kind> --compact
  3. sigmalifting-cli template <kind> --compact
  4. sigmalifting-cli validate <kind> --file <path|"-"> --compact

Use the template to learn field shape, defaults, sentinel values, and nesting. Use schema show to check constraints. Use this skill to decide what the program should mean structurally.

If the skill and CLI appear to disagree, trust the CLI schema and report the skill as stale.

Do not invent fields that are not present in the CLI schema or template.

Authoritative Sample Workflow

If the user provides an exported SigmaLifting JSON file, treat that export as the first source of truth.

Before generating or translating anything similar:

  1. identify the bundle kind the file actually matches
  2. run the standalone CLI against the file exactly as provided
  3. validate it first
  4. if validation reports repair warnings, normalize it and validate the normalized output
  5. only then extract modeling rules from it
  6. make any changes through CLI mutation commands, never by patching the JSON file

If an app-exported file cannot be consumed by the standalone CLI, treat that as a CLI problem to investigate before declaring the modeling wrong.

Do not skip this step and jump straight to reconstructing the program from memory, public spreadsheets, or a simplified interpretation.

Block Semantics

Do not define a block by contiguous time alone.

A block is a maximal consecutive run of weeks that share the same structural skeleton.

The structural skeleton means:

  • same training day layout
  • same exercise identities on each day
  • same set-group count and ordering per exercise
  • same variable-parameter style per set group
  • same dependency shape such as backoff or fatigue-drop relationships

What may vary inside a block:

  • weekly set counts
  • weekly reps
  • weekly RPE values
  • weekly percentages
  • weekly notes

What should usually force a new block:

  • a day appears, disappears, or changes role materially
  • an exercise is added, removed, or replaced
  • a set group appears or disappears
  • a set group changes semantic role rather than just numeric values
  • dependency structure changes
  • the week only fits by abusing placeholder zero-sets across many exercises
  • the phase intent clearly changes even if the schema could be compressed

Do not collapse an entire multi-week program into one block just because weekly arrays can encode it.

That is a schema-valid compression, but it is a modeling error under SigmaLifting semantics.

Variable Parameter Semantics

Every set group has exactly one workout-recorded variable parameter: weight, reps, or rpe.

The other two training numbers are prescribed by the program:

  • variable_parameter: "weight" means reps and RPE are prescribed, and weight is recorded during the workout.
  • variable_parameter: "reps" means weight and RPE are prescribed, and reps are recorded during the workout.
  • variable_parameter: "rpe" means weight and reps are prescribed, and RPE is recorded during the workout.

Do not model a set group by prescribing all three numbers. Do not leave two numbers open unless the CLI has a command and schema support for that explicit behavior.

Backoff and fatigue-drop configs are RPE-variable tools in the app model. They are only valid on set groups with variable_parameter: "rpe". If weight is the variable parameter, do not enable backoff_config, fatigue_drop_config, or mixed-weight prescription.

Workflow

When modeling a program:

  1. Inspect each week for structural sameness, not just duration.
  2. Group only consecutive weeks that share the same skeleton.
  3. Create one block per structural group.
  4. Use weekly arrays only for parameter variation inside that block.
  5. Preserve special-case instructions in notes if they are not truly machine-derived.
  6. If unsure, prefer more blocks over fewer blocks.

Warning Signs

Stop and re-evaluate the block split if you notice:

  • many 0 set placeholders just to make weeks fit
  • weeks that feel like distinct phases but are still in one block
  • day layouts drifting across weeks
  • exercise schemes changing identity from week to week

References

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