Technical Analyst
tradermonty/claude-trading-skills
This skill should be used when analyzing weekly price charts for stocks, stock indices, cryptocurrencies, or forex pairs.
A skill your agent uses when a startup needs an evidence-weighted health check, investor lens, runway diagnosis, top constraint, or cheapest next validation test.
Install Startup Evaluation
$ npx skills add Mark393295827/third-brain-v7-skills --skill startup-evaluation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Mark393295827/third-brain-v7-skills startup-evaluation --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/Mark393295827/third-brain-v7-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/startup-evaluation .claude/skills/startup-evaluation && rm -rf skills-srcUse ~/.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/
Install the "startup-evaluation" agent skill from https://github.com/Mark393295827/third-brain-v7-skills/tree/main/skills/startup-evaluation into .claude/skills/startup-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "startup-evaluation", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/Mark393295827/third-brain-v7-skills/tree/main/skills/startup-evaluationType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add Mark393295827/third-brain-v7-skills --skill startup-evaluation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Mark393295827/third-brain-v7-skills startup-evaluation --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Mark393295827/third-brain-v7-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/startup-evaluation .agents/skills/startup-evaluation && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "startup-evaluation" agent skill from https://github.com/Mark393295827/third-brain-v7-skills/tree/main/skills/startup-evaluation into .agents/skills/startup-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "startup-evaluation", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Mark393295827/third-brain-v7-skills --skill startup-evaluation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Mark393295827/third-brain-v7-skills startup-evaluation --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Mark393295827/third-brain-v7-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/startup-evaluation .cursor/skills/startup-evaluation && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "startup-evaluation" agent skill from https://github.com/Mark393295827/third-brain-v7-skills/tree/main/skills/startup-evaluation into .cursor/skills/startup-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "startup-evaluation", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/Mark393295827/third-brain-v7-skills.git --path skills/startup-evaluation--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add Mark393295827/third-brain-v7-skills --skill startup-evaluation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Mark393295827/third-brain-v7-skills startup-evaluation --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Mark393295827/third-brain-v7-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/startup-evaluation .gemini/skills/startup-evaluation && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "startup-evaluation" agent skill from https://github.com/Mark393295827/third-brain-v7-skills/tree/main/skills/startup-evaluation into .gemini/skills/startup-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "startup-evaluation", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install Mark393295827/third-brain-v7-skills startup-evaluationInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add Mark393295827/third-brain-v7-skills --skill startup-evaluation -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Mark393295827/third-brain-v7-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/startup-evaluation .github/skills/startup-evaluation && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "startup-evaluation" agent skill from https://github.com/Mark393295827/third-brain-v7-skills/tree/main/skills/startup-evaluation into .github/skills/startup-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "startup-evaluation", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Mark393295827/third-brain-v7-skills --skill startup-evaluation -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Mark393295827/third-brain-v7-skills startup-evaluation --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Mark393295827/third-brain-v7-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/startup-evaluation .opencode/skills/startup-evaluation && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "startup-evaluation" agent skill from https://github.com/Mark393295827/third-brain-v7-skills/tree/main/skills/startup-evaluation into .opencode/skills/startup-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "startup-evaluation", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
startup-evaluation- GitHub stars
- 141
- Token cost
- ~1.4k tokens
- SKILL.md length
- 652 words
- Files
- 2 (incl. references)
- Skills in repo
- 21
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when a startup needs an evidence-weighted health check, investor lens, runway diagnosis, top constraint, or cheapest next validation test.
- Works in 8 steps: Rank demand evidence from belief and… → Score eight dimensions using… → For investor work, cross-check 5T: Team,… → …
- A startup needs an evidence-weighted health check
- SKILL.md covers Usage Template, Workflow, Failure Protocol and Output Contract, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Startup Evaluation is an agent skill from Mark393295827/third-brain-v7-skills. Use when a startup needs an evidence-weighted health check, investor lens, runway diagnosis, top constraint, or cheapest next validation test.
Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/evaluation-rubric.md`).
It sits in Business, Finance & HR. The repository describes itself as: agent wiki +engineering skills. The licence is MIT.
When your agent uses it
- A startup needs an evidence-weighted health check
- Runway diagnosis
- Cheapest next validation test
Example prompts
- “/startup-evaluation”
Workflow steps
8 steps, taken from the first numbered list in SKILL.md.
- Rank demand evidence from belief and interviews through behavior, payment, retention, expansion, and referral.
- Score eight dimensions using stage-adjusted weights: pain/beachhead, market/timing, value step-change, PMF/traction, business…
- For investor work, cross-check 5T: Team, Target Market, Tech/Product, Traction, Terms.
- For AI-native or hard-tech cases, test what remains defensible as components cheapen and identify physical, regulatory, deployment, or…
- Separate the spending engine (CapEx, inference, integration, service labor,
- Diagnose runway and whether spend buys evidence for the next milestone.
- Name the single constraint most likely to invalidate or unlock the company.
- Specify the cheapest test, threshold, owner, budget, and stop condition.
What it can do on your machine
Read from SKILL.md and the folder at commit 5a64514. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
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
Startup Evaluation loads about 1.4k tokens when it runs, and up to ~2.3k if it reads all its reference files. Until then it costs about 40 tokens; SKILL.md has 652 words of instructions outside code blocks.
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 Mark393295827/third-brain-v7-skills at commit 5a64514, republished under its MIT licence (© Mark393295827). 652 words, ~1,424 tokens.
Download SKILL.mdSave it as
.claude/skills/startup-evaluation/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.- name
- startup-evaluation
- description
- Use when a startup needs an evidence-weighted health check, investor lens, runway diagnosis, top constraint, or cheapest next validation test.
- metadata.version
- 8.1.0
- metadata.updated
- 2026-08-18
- metadata.profile
- one-shot
- metadata.assumes
- The company stage, business type, and at least partial customer or operating evidence can be obtained.
- metadata.conflicts_with
- Treating pitch quality, market size, or founder conviction as proof of demand or investment merit.
Startup Evaluation
<skill_contract>
<input>Company, stage, evaluation decision, customer evidence, traction, economics, team, runway, terms, and risks.</input>
<output>An evidence-weighted health, venture-suitability, and financing assessment with one top constraint and cheapest test.</output>
<done>Every score and verdict traces to evidence, fatal risks remain visible, and the next test has owner, threshold, budget, and stop.</done>
<non_goals>Investment advice by narrative, averaging away fatal risk, or treating market size, conviction, or pitch quality as demand.</non_goals>
Evaluate the company the evidence supports, not the story it tells. Distinguish business health, venture suitability, and financing readiness; they are different decisions.
Usage Template
Provide: company, stage, startup type, evaluation decision, customer, problem, product, traction, team, economics, runway, round terms, and known risks. Use the rubric in references/evaluation-rubric.md when scoring is requested.
Workflow
<intake>Classify stage, type (SME, innovation-driven, venture-scale, hard-tech, AI-native), lens (founder, diligence, fundraising, pivot), and evidence state. Define the decision and time horizon before calculating a score.
</intake><unknowns_gate>
Separate facts, assumptions, self-reported claims, and missing evidence. If the target decision or company identity is unclear, return NEEDS_INPUT. Continue with missing metrics only when the output is explicitly provisional and each gap has a probe.
</unknowns_gate>
<execute>- Rank demand evidence from belief and interviews through behavior, payment, retention, expansion, and referral.
- Score eight dimensions using stage-adjusted weights: pain/beachhead, market/timing, value step-change, PMF/traction, business model/economics, team/governance, capital/runway, and moat/risk.
- For investor work, cross-check 5T: Team, Target Market, Tech/Product, Traction, Terms.
- For AI-native or hard-tech cases, test what remains defensible as components cheapen and identify physical, regulatory, deployment, or supply-chain bottlenecks. For AI value capture, separate usage, productivity, customer ROI, and vendor profit; do not infer durable economics from token volume or revenue growth alone.
- Separate the spending engine (CapEx, inference, integration, service labor, energy, and deployment cost) from the earning engine (retention, expansion, pricing power, gross margin, and free cash flow). Test who owns institutional learning: workflow exceptions, context, permissions, and feedback write-back.
- Diagnose runway and whether spend buys evidence for the next milestone.
- Name the single constraint most likely to invalidate or unlock the company.
- Specify the cheapest test, threshold, owner, budget, and stop condition.
Do not average away fatal risk. A healthy cash-flow business may still be a poor venture investment; a large market cannot rescue absent demand evidence.
</execute><evaluate>Trace every score and verdict to the evidence ledger. Stress-test the conclusion against churn, paid acquisition dependence, founder conflict, financing timing, platform dependency, falling model prices, rising inference/service cost, and customer ROI that fails to become vendor margin. Calibrate confidence to the weakest decision-critical claim.
</evaluate>Show full SKILL.md (223 more words)Show less
Failure Protocol
NEEDS_INPUT: the evaluation decision, stage, or company boundary is unclear.INSUFFICIENT_EVIDENCE: the requested verdict depends on unavailable demand, retention, economics, or terms data.VERIFY_FAILED: a score lacks evidence or contradicts the ledger; rescore or mark unknown.BUDGET_STOP: return the provisional constraint and highest-value evidence request.
Output Contract
Return status, result (verdict, scorecard, top constraint, fatal risks, and next test), evidence (fact/assumption ledger), unknowns, and next_action with owner and threshold.
Edge Cases
- Pre-revenue company has no retention data: do not assign traction maturity; score the available behavioral test and make payment/usage the next gate.
- Bootstrapped company has strong cash flow but a small market: rate business health separately from venture-scale suitability.
- AI usage grows while gross margin and customer retention fall: record adoption without calling it value capture; test pricing, service labor, and inference economics separately.
Success Metrics
- Stage, type, decision lens, and evidence maturity are explicit.
- Verdict confidence follows observed behavior rather than narrative polish.
- AI-native verdicts distinguish adoption, customer value, and supplier profit.
- One top constraint and one cheap falsifiable test govern the recommendation.
Quality Gates
- Facts, assumptions, self-reports, and missing evidence are separated.
- Score weights fit stage and business type.
- Fatal risks are not hidden by averages.
- AI cases separate spending, usage, productivity, customer ROI, and vendor profit.
- Runway, milestone, test threshold, owner, and stop condition are explicit.
</skill_contract>
© Mark393295827, 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 1 other file (references) in skills/startup-evaluation of Mark393295827/third-brain-v7-skills.
- SKILL.md
- references/evaluation-rubric.md
Open the folder on GitHubat commit 5a64514
Compare with similar skills
Startup Evaluation next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Startup Evaluation this skillMark393295827/third-brain-v7-skills | 141 | — | ~1.4k | Automated safety check: Pass | MIT | |
| Technical Analysttradermonty/claude-trading-skills | 3k | 5 repos | ~4.6k | Automated safety check: Pass | MIT | |
| Creating Financial ModelsChen-zexi/open-ptc-agent | 729 | 4 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Stock APIzhangxiangliang/stock-api | 2k | — | ~507 | Automated safety check: Pass | MIT | |
| Theme Detectortradermonty/claude-trading-skills | 3k | 2 repos | ~4.9k | Automated safety check: Pass | MIT | |
| Itr Walakaranb192/itr-wala | 871 | — | ~3.6k | Automated safety check: Pass | MIT |
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Questions about Startup Evaluation
What does Startup Evaluation do?
A skill your agent uses when a startup needs an evidence-weighted health check, investor lens, runway diagnosis, top constraint, or cheapest next validation test. Startup Evaluation is an agent skill from Mark393295827/third-brain-v7-skills. Use when a startup needs an evidence-weighted health check, investor lens, runway diagnosis, top constraint, or cheapest next validation test.
When should I use Startup Evaluation?
Startup Evaluation fits situations like: A startup needs an evidence-weighted health check; runway diagnosis; cheapest next validation test.
How do I install Startup Evaluation in Claude Code?
Run `npx skills add Mark393295827/third-brain-v7-skills --skill startup-evaluation -a claude-code`. Or copy the skill folder (skills/startup-evaluation in Mark393295827/third-brain-v7-skills) into .claude/skills/startup-evaluation in your project. Claude Code loads it when a task matches its description.
How do I install Startup Evaluation in Codex?
Run `npx skills add Mark393295827/third-brain-v7-skills --skill startup-evaluation -a codex`. Or copy the skill folder (skills/startup-evaluation in Mark393295827/third-brain-v7-skills) into .agents/skills/startup-evaluation in your project. Codex loads it when a task matches its description.
Can I use Startup Evaluation 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 Mark393295827/third-brain-v7-skills --skill startup-evaluation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/startup-evaluation, .gemini/skills/startup-evaluation, .github/skills/startup-evaluation and .opencode/skills/startup-evaluation in your project.
What does Startup Evaluation need to run?
SKILL.md names no scripts, command-line tools or credentials: Startup Evaluation is instructions for the agent only.
Does Startup Evaluation 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 Startup Evaluation 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 Startup Evaluation use?
Startup Evaluation 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 Startup Evaluation use?
About 1.4k tokens (SKILL.md is roughly 5.7k 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 921 tokens, read only when the agent opens those files.
What are the alternatives to Startup Evaluation?
Skills that share tags, products or a category with Startup Evaluation: Technical Analyst (tradermonty/claude-trading-skills, 3k stars), Creating Financial Models (Chen-zexi/open-ptc-agent, 729 stars), Stock API (zhangxiangliang/stock-api, 2k stars) and Theme Detector (tradermonty/claude-trading-skills, 3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Startup Evaluation?
Mark393295827 (a GitHub user) maintains it in Mark393295827/third-brain-v7-skills, which has 141 GitHub stars. The repository holds 21 skills in this directory. The repository was last updated on September 19, 2026.
Source: Mark393295827/third-brain-v7-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.