feasibility-check

feasibility-check is a skill for Claude Code, Codex from yogsoth-ai/north-star-crystallization. It costs 39 tokens per session (189 once invoked), scanned A, original, Apache-2.0.

A feasibility-review helper that checks a goal tree against a person’s abilities, known barriers, and deadline. It labels each branch feasible, a stretch, or infeasible, and can suggest alternative paths.

In plain words
What is it for?
Use it after breaking a research direction into goals to test each branch. It helps select workable alternatives and identify goals that need reconsideration.
Why use it?
It catches plans that look sensible but cannot be completed with the available skills, resources, or time. This lets you adjust the plan before pursuing it.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions subagents.

Good fit Use it after breaking a research direction into goals to test each branch. It helps select workable alternatives and identify goals that need reconsideration.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/yogsoth-ai/north-star-crystallization/feasibility-check
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add yogsoth-ai/north-star-crystallization --skill feasibility-check
Clone the repo
git clone --depth 1 https://github.com/yogsoth-ai/north-star-crystallization

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for feasibility-check

README.md
[![agentmods](https://agentmods.dev/badge/skills/yogsoth-ai/north-star-crystallization/feasibility-check/github.svg)](https://agentmods.dev/skills/yogsoth-ai/north-star-crystallization/feasibility-check)
Your own site
<a href="https://agentmods.dev/skills/yogsoth-ai/north-star-crystallization/feasibility-check"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/north-star-crystallization/feasibility-check/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for feasibility-check

Your own site · 80×15
<a href="https://agentmods.dev/skills/yogsoth-ai/north-star-crystallization/feasibility-check"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/north-star-crystallization/feasibility-check.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 189 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00039 $0.00189
Opus 5 $0.00019 $0.00095
Sonnet 5 $0.00008 $0.00038
Haiku 4.5 $0.00004 $0.00019

Measured 9d ago against content hash d84e08493b82, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

feasibility-check scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/feasibility-check/SKILL.md · 32 lines

What it actually says

Feasibility Check

Reality-check the GoalTree against the user's actual situation.

Execution

Subagent — spawned via subagent-spawning/spawn-agent skill.

Input

  • GoalTree (full structure)
  • ActorProfile
  • ObstacleReport

Checks Against

  • ActorProfile: Can this user do each leaf?
  • ObstacleReport: Are known barriers addressed?
  • Timeline: Can it be done in time?

Output

Feasibility assessment per branch — feasible / stretch / infeasible + reasoning. For infeasible paths: suggest OR alternatives.

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 32 lines · 39 tokens per session scan A d84e08493b82

Subscribe to this mod's changes

feasibility-check is a skill published in the GitHub repository yogsoth-ai/north-star-crystallization (2 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 39 tokens to every session and 189 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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