Agent skill

Feasibility Study

by sd0xdev in sd0xdev/sd0x-harness

Feasibility analysis from first principles. An agent skill from sd0xdev/sd0x-harness.

MITAuto-check passedDevelopment

Install Feasibility Study

skills CLI
$ npx skills add sd0xdev/sd0x-harness --skill feasibility-study -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install sd0xdev/sd0x-harness feasibility-study --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/sd0xdev/sd0x-harness.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/feasibility-study .claude/skills/feasibility-study && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
feasibility-study
GitHub stars
192
Token cost
~1.9k tokens
SKILL.md length
749 words
Files
4 (incl. references)
Skills in repo
91
Repo updated
First seen
Licence
MIT

At a glance

Feasibility analysis from first principles. An agent skill from sd0xdev/sd0x-harness.

  • Works in 7 steps: Resolve the feature context → Requirement Decomposition → Constraint Analysis → …
  • : evaluating solutions before tech-spec
  • SKILL.md covers Supplementary Agent, Trigger, When NOT to Use and Workflow, plus 6 more sections
  • Calls node

What it does

Feasibility Study is an agent skill from sd0xdev/sd0x-harness. Feasibility analysis from first principles. Use when: evaluating solutions before tech-spec, comparing approaches, risk assessment. Not for: implementation (use feature-dev), architecture advice (use codex-architect). Output: quantitative comparison + recommendation.

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `references/analysis-phases.md`, `references/codex-discussion-guide.md` and `references/output-template.md`).

It sits in Development. The repository describes itself as: The harness layer for Claude Code — a reference implementation of harness engineering with hook-enforced dual review, state-machine gates that survive context compaction, and… The licence is MIT.

When your agent uses it

  • : evaluating solutions before tech-spec
  • Comparing approaches
  • Risk assessment

Example prompts

  • “/feasibility-study”

Requirements

  • Pre-approved tools (allowed-tools): Read, Grep, Glob, Bash(git:*), Bash(bash:*), Write, Agent, Bash(node:*)

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Resolve the feature context
  2. Requirement Decomposition
  3. Constraint Analysis
  4. Code Research
  5. Solution Exploration
  6. In-Depth Codex Discussion
  7. Comparative Decision

What it can do on your machine

Read from SKILL.md and the folder at commit c9a2036. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Grep
    • Glob
    • Bash(git:*)
    • Bash(bash:*)
    • Write
    • Agent
    • Bash(node:*)

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • node

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Feasibility Study loads about 1.9k tokens when it runs, and up to ~4.1k if it reads all its reference files. Until then it costs about 71 tokens; SKILL.md has 749 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~71
When it runs · the whole SKILL.md, loaded when a task matches
~1.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from sd0xdev/sd0x-harness at commit c9a2036, republished under its MIT licence (© sd0xdev). 749 words, ~1,873 tokens.

Download SKILL.mdSave it as .claude/skills/feasibility-study/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
feasibility-study
description
Feasibility analysis from first principles. Use when: evaluating solutions before tech-spec, comparing approaches, risk assessment. Not for: implementation (use feature-dev), architecture advice (use codex-architect). Output: quantitative comparison + recommendation.
allowed-tools
Read, Grep, Glob, Bash(git:*), Bash(bash:*), Write, Agent, Bash(node:*)

Feasibility Study Skill

Supplementary Agent

For each solution option, dispatch background exploration:

Agent({ description: "Explore feasibility of solution option", subagent_type: "feasibility-analyst", prompt: Research the feasibility of: <solution description> Evaluate technical feasibility, effort, risk, extensibility, and maintenance cost. })

Trigger

  • Keywords: feasibility, is this possible, can we, should we, explore options, before tech spec

When NOT to Use

  • Already have a tech spec (use /deep-analyze)
  • Need implementation, not analysis (use /codex-implement)
  • Quick question (use /codex-explain or /codex-architect)

Workflow

Resolve → Decompose → Constraints → Code research → Solutions → Codex discussion → Decision → Report
Phase 0: Resolve the feature context

The sets Phase 1 reads have to come from somewhere, and this skill is invoked directly (/feasibility-study <topic>) as often as it is invoked from another skill — so it resolves them itself rather than assuming a caller supplied them:

bash
# The node entrypoint. The shell wrapper's own header tells skills to prefer this one once they hold
# `Bash(node:*)` — and this skill now does, for its transport dispatches. The wrapper was named here
# only while that grant was absent; keeping it afterwards would have instructed a second-choice
# entrypoint for a reason that had stopped being true.
node scripts/resolve-feature.js [--feature <key>]

The reply is one JSON document. What this skill reads out of it: scan_error first — the gate below decides whether anything else in the payload means what it says — then current_authority (what the system does today) and the design_records entries — design records carry the rationale; it is the type: requirements subset of them that states what was asked for, which is why Phase 1 filters before it selects. Each entry is { file, type, namespace, confidence, is_canonical, role }, file relative to docs_path. An empty or non-JSON reply is a failure too — node may be unavailable, which the shim cannot report as a payload. Treat it exactly as scan_error !== false below.

Phase 1: Requirement Decomposition

Input source priority:

  1. If a requirements doc resolves from design_records → consume as the authoritative statement of what was asked for, validate via 5-Why. It is a design record, not a description of current behaviour: for "what does the system do today", read code, rules/ and current_authority
  2. Otherwise → extract requirements from user input via 5-Why analysis

design_records is an array, so "a requirements doc" needs a rule rather than an assumption — a split or variant-backed phase contributes more than one. Filter to type: requirements first, then:

#Candidates (design_records where type: requirements)Result
1nonePath 2 — extract from user input. A feature with no requirements doc is a normal state, not an exit
2exactly onethat one
3two or more, exactly one with is_canonical: truethat one
4two or more, and none or several canonicalGate: Need Human, naming the candidates

Rows 1 and 4 are different answers: "there is none" is acted on, "there are two" must not be resolved by picking. The same order /architecture applies to its tech-spec candidates.

scan_error gate. Gate on scan_error !== false, not on scan_error === true. When it is not exactly false the four source sets are unknown, not empty — the corpus could not be enumerated (unreadable directory, broken taxonomy, no repository), or the resolver never ran and a shell fallback supplied a payload with no such field at all. {} is the shape that made the stricter test useless: it has no scan_error, so === true is false and the gate passes a payload that contains nothing. Do not proceed as though the feature has no authority documents — report and take the ⚠️ Need Human exit. A key may still be present, so a non-null key is not evidence the sets are complete.

Use "5 Why" to uncover essence:

  1. Surface requirement (what user asks for)
  2. Underlying problem (why they need it)
  3. Success criteria (quantifiable acceptance)
Show full SKILL.md (199 more words)Show less
Phase 2: Constraint Analysis

Inventory constraints by type (Technical, Business, Resource, Compatibility) with flexibility rating.

Phase 3: Code Research

Research existing codebase:

  • Related modules and reusable logic
  • Existing design patterns
  • Tech debt to work around
Phase 4: Solution Exploration

Brainstorm 2-3+ solutions, each with:

  1. Core idea (one sentence)
  2. Implementation path
  3. Quantified feasibility (see references/analysis-phases.md)
  4. Cost and trade-offs
Phase 5: In-Depth Codex Discussion

⚠️ Core step — not optional (unless --no-codex) ⚠️

See references/codex-discussion-guide.md for full rules and examples.

ToolPurposeWhen
/codex-brainstormEnumerate all optionsAt start
/codex-architectEvaluate designAfter proposal forms
@skills/codex-code-review/references/codex-transport.md § ResumeAsk detailsAnytime
Phase 6: Comparative Decision

Side-by-side comparison → recommendation + backup + open questions.

Evaluation Dimensions

DimensionGreenYellowRed
Technical FeasibilityHas existing patternsNeeds adaptationMajor innovation
Effort< 3 person-days3-10 person-days> 10 person-days
RiskSmall scopeSome uncertaintyMany unknowns
ExtensibilityEasy to extendNeeds refactoringHard to extend
Maintenance CostClean, easySome complexityComplex

Output

markdown
## Feasibility Study: <title>
### Quantitative Comparison
| Criterion | Option A | Option B | Option C |
|-----------|----------|----------|----------|

### Recommendation
<selected option with rationale>

Verification

  • 5 Why decomposition completed
  • Constraints inventoried with flexibility
  • Existing code researched (grep/read)
  • 2-3+ solutions explored with quantified assessment
  • Codex discussion documented (unless --no-codex)
  • Comparison table + recommendation + open questions

References

  • Analysis phases: references/analysis-phases.md
  • Codex discussion: references/codex-discussion-guide.md
  • Output template: references/output-template.md

Relationship with Other Commands

/feasibility-study → /tech-spec → /deep-analyze → /codex-implement

Examples

Input: /feasibility-study "Add user quota management"
Action: 5 Why → constraints → code research → 3 solutions → Codex discussion → recommendation

Input: /feasibility-study "Optimize cache" --context src/service/cache.ts
Action: Read cache code → constraints → solutions → Codex brainstorm → comparison → report

© sd0xdev, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (references) in skills/feasibility-study of sd0xdev/sd0x-harness.

  • SKILL.md
  • references/analysis-phases.md
  • references/codex-discussion-guide.md
  • references/output-template.md

Open the folder on GitHubat commit c9a2036

Compare with similar skills

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Code Review ChecklistshareAI-lab/learn-claude-code78k5 repos~1.1kAutomated safety check: PassMIT
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Categories

Questions about Feasibility Study

What does Feasibility Study do?

Feasibility analysis from first principles. An agent skill from sd0xdev/sd0x-harness. Feasibility Study is an agent skill from sd0xdev/sd0x-harness. Feasibility analysis from first principles.

When should I use Feasibility Study?

Feasibility Study fits situations like: : evaluating solutions before tech-spec; comparing approaches; risk assessment.

How do I install Feasibility Study in Claude Code?

Run `npx skills add sd0xdev/sd0x-harness --skill feasibility-study -a claude-code`. Or copy the skill folder (skills/feasibility-study in sd0xdev/sd0x-harness) into .claude/skills/feasibility-study in your project. Claude Code loads it when a task matches its description.

How do I install Feasibility Study in Codex?

Run `npx skills add sd0xdev/sd0x-harness --skill feasibility-study -a codex`. Or copy the skill folder (skills/feasibility-study in sd0xdev/sd0x-harness) into .agents/skills/feasibility-study in your project. Codex loads it when a task matches its description.

Can I use Feasibility Study in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add sd0xdev/sd0x-harness --skill feasibility-study -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/feasibility-study, .gemini/skills/feasibility-study, .github/skills/feasibility-study and .opencode/skills/feasibility-study in your project.

What does Feasibility Study need to run?

Going by SKILL.md and its folder, Feasibility Study needs the command-line tools its instructions call (node). Its frontmatter pre-approves these tools: Read, Grep, Glob, Bash(git:*), Bash(bash:*), Write, Agent, Bash(node:*).

Does Feasibility Study access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Feasibility Study safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Feasibility Study use?

Feasibility Study is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Feasibility Study use?

About 1.9k tokens (SKILL.md is roughly 7.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.2k tokens, read only when the agent opens those files.

What are the alternatives to Feasibility Study?

Skills that share tags, products or a category with Feasibility Study: Finishing a Development Branch (obra/superpowers, 296k stars), Typescript Advanced Types (rolling-scopes/rsschool-app, 10k stars), PR Babysitter (openinterpreter/openinterpreter, 69k stars) and Code Review Checklist (shareAI-lab/learn-claude-code, 78k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Feasibility Study?

sd0xdev (a GitHub user) maintains it in sd0xdev/sd0x-harness, which has 192 GitHub stars. The repository holds 91 skills in this directory. The repository was last updated on October 6, 2026.

Source: sd0xdev/sd0x-harness on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.