Score and compare covariance estimates with precise's assessor panel.
$ npx skills add microprediction/precise --skill score-covariance-estimate -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install microprediction/precise score-covariance-estimate --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/microprediction/precise.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/score-covariance-estimate .claude/skills/score-covariance-estimate && 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 "score-covariance-estimate" agent skill from https://github.com/microprediction/precise/tree/main/.claude/skills/score-covariance-estimate into .claude/skills/score-covariance-estimate/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "score-covariance-estimate", 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/microprediction/precise/tree/main/.claude/skills/score-covariance-estimateType 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 microprediction/precise --skill score-covariance-estimate -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install microprediction/precise score-covariance-estimate --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microprediction/precise.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/score-covariance-estimate .agents/skills/score-covariance-estimate && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "score-covariance-estimate" agent skill from https://github.com/microprediction/precise/tree/main/.claude/skills/score-covariance-estimate into .agents/skills/score-covariance-estimate/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "score-covariance-estimate", 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 microprediction/precise --skill score-covariance-estimate -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install microprediction/precise score-covariance-estimate --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microprediction/precise.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/score-covariance-estimate .cursor/skills/score-covariance-estimate && 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 "score-covariance-estimate" agent skill from https://github.com/microprediction/precise/tree/main/.claude/skills/score-covariance-estimate into .cursor/skills/score-covariance-estimate/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "score-covariance-estimate", 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/microprediction/precise.git --path .claude/skills/score-covariance-estimate--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 microprediction/precise --skill score-covariance-estimate -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install microprediction/precise score-covariance-estimate --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microprediction/precise.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/score-covariance-estimate .gemini/skills/score-covariance-estimate && 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 "score-covariance-estimate" agent skill from https://github.com/microprediction/precise/tree/main/.claude/skills/score-covariance-estimate into .gemini/skills/score-covariance-estimate/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "score-covariance-estimate", 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 microprediction/precise score-covariance-estimateInstalls 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 microprediction/precise --skill score-covariance-estimate -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/microprediction/precise.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/score-covariance-estimate .github/skills/score-covariance-estimate && 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 "score-covariance-estimate" agent skill from https://github.com/microprediction/precise/tree/main/.claude/skills/score-covariance-estimate into .github/skills/score-covariance-estimate/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "score-covariance-estimate", 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 microprediction/precise --skill score-covariance-estimate -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install microprediction/precise score-covariance-estimate --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microprediction/precise.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/score-covariance-estimate .opencode/skills/score-covariance-estimate && 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 "score-covariance-estimate" agent skill from https://github.com/microprediction/precise/tree/main/.claude/skills/score-covariance-estimate into .opencode/skills/score-covariance-estimate/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "score-covariance-estimate", 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.
score-covariance-estimateScore and compare covariance estimates with precise's assessor panel.
Score Covariance Estimate is an agent skill from microprediction/precise. Score and compare covariance estimates with precise's assessor panel. Use when you need to judge an estimate out-of-sample or rank competing estimators — and especially in high dimensions, where the plain held-out likelihood is misleading.
Its SKILL.md is about 640 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
The repository describes itself as: Online Covariance and Correlation Estimation. The licence is MIT.
Read from SKILL.md and the folder at commit 2a193c0. It shows what the files ask for, not the result of running them.
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.
No scripts in the folder and no shell commands in SKILL.md (its code samples are python).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Score Covariance Estimate loads about 641 tokens when it runs. Until then it costs about 66 tokens; SKILL.md has 263 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.
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.
The full file from microprediction/precise at commit 2a193c0, republished under its MIT licence (© microprediction). 263 words, ~641 tokens.
.claude/skills/score-covariance-estimate/SKILL.md (or your agent's skills folder).from precise import all_assessors, assessor_from_name
for A in all_assessors():
s = A().score(cov, X_test=X_test, true_cov=Sigma_true) # higher = bettercov is the estimate to judge; X_test is held-out data (rows = observations); true_cov is the
population covariance (only available in simulation).needs_data and needs_truth; pass what it needs. Truth-free assessors work on
real data, truth-requiring ones (e.g. FrobeniusToTruth) only in simulation.Do not rank estimators by the held-out Gaussian log-likelihood when p is comparable to n. The
likelihood is dominated by the smallest, unidentifiable eigenvalues of the estimate; empirically it ranks
estimators below chance in that regime. Instead use inversion-free or block judges:
| Regime / goal | Use |
|---|---|
| low dimension, well-conditioned | LogLikelihood (it is optimal here) |
high dimension (p/n near 1 or larger) | BlockPseudoLikelihood, SchurLikelihood, VariogramScore, FrobeniusToTruth (sim only) |
| economic / portfolio relevance | GMVVariance (out-of-sample minimum-variance variance) |
| forecasting a variance from a noisy proxy | a QLIKE / Bregman-consistent loss, not RMSE on the proxy — RMSE on a noisy variance proxy can rank inconsistently |
SchurLikelihood(gamma=...) is a tunable bridge: gamma=1 is the full likelihood (fragile in high-d),
gamma=0 the robust block-diagonal one, interior values better-conditioned than either.
© microprediction, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in .claude/skills/score-covariance-estimate of microprediction/precise.
Open the folder on GitHubat commit 2a193c0
Score Covariance Estimate 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 |
|---|---|---|---|---|---|---|
| Score Covariance Estimate this skillmicroprediction/precise | 337 | — | ~641 | Automated safety check: Pass | MIT | |
| Estimate Immune Score Analysisaipoch/medical-research-skills | 1.9k | — | ~3.1k | Automated safety check: Pass | MIT | |
| Claw Scoreopenclaw/openclaw | 392k | — | ~2.5k | Automated safety check: Pass | MIT | |
| Harness Scoreruvnet/ruflo | 74k | — | ~605 | Automated safety check: Notes | MIT | |
| Task Effort EstimatorDonchitos/Claude-Code-Game-Studios | 26k | — | ~1.2k | Automated safety check: Pass | MIT | |
| Score Evalsickn33/agentic-awesome-skills | 47k | 1 repos | ~304 | Automated safety check: Pass | MIT |
aipoch/medical-research-skills
A skill your agent uses to compute ESTIMATE immune-related microenvironment scores from a bulk expression matrix, generate an ESTIMATE score heatmap, and optionally generate group-wise ESTIMATE…
openclaw/openclaw
Audit or refresh OpenClaw maturity scorecard docs from root taxonomy, maturity scores, and QA evidence artifacts without using maintainer discrawl data or committed inventory reports.
ruvnet/ruflo
5-dimension harness readiness scorecard from metaharness score {path}.
Donchitos/Claude-Code-Game-Studios
Estimates the effort for a game development task from code complexity, scope, risk and past sprint data, returning a range with a confidence level.
sickn33/agentic-awesome-skills
Imported skill score-eval from upstream source. An agent skill from sickn33/agentic-awesome-skills.
sickn33/agentic-awesome-skills
Estimate AI-assisted and hybrid human+agent development work with research-backed PERT statistics and calibration feedback loops
microprediction/precise
Pick which precise covariance estimator to use for a given dataset.
microprediction/precise
Estimate a covariance / correlation / precision matrix incrementally with precise.
microprediction/precise
Maintain an online covariance over named series whose set changes over time (e.g.
microprediction/precise
Online (incremental) covariance, correlation, and precision estimation in Python — the streaming complement to sklearn.covariance.
microprediction/precise
Rigorously and honestly assess a NEW or proposed covariance / correlation / precision estimator, or a new covariance scoring rule, using precise.
Score and compare covariance estimates with precise's assessor panel. Score Covariance Estimate is an agent skill from microprediction/precise. Score and compare covariance estimates with precise's assessor panel.
Score Covariance Estimate fits situations like: you need to judge an estimate out-of-sample; rank competing estimators — and especially in high dimensions; where the plain held-out likelihood is misleading.
Run `npx skills add microprediction/precise --skill score-covariance-estimate -a claude-code`. Or copy the skill folder (.claude/skills/score-covariance-estimate in microprediction/precise) into .claude/skills/score-covariance-estimate in your project. Claude Code loads it when a task matches its description.
Run `npx skills add microprediction/precise --skill score-covariance-estimate -a codex`. Or copy the skill folder (.claude/skills/score-covariance-estimate in microprediction/precise) into .agents/skills/score-covariance-estimate in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add microprediction/precise --skill score-covariance-estimate -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/score-covariance-estimate, .gemini/skills/score-covariance-estimate, .github/skills/score-covariance-estimate and .opencode/skills/score-covariance-estimate in your project.
SKILL.md names no scripts, command-line tools or credentials: Score Covariance Estimate is instructions for the agent only. Our summary lists: Python 3.
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.
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.
Score Covariance Estimate is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 641 tokens (SKILL.md is roughly 2.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Score Covariance Estimate: Estimate Immune Score Analysis (aipoch/medical-research-skills, 1.9k stars), Claw Score (openclaw/openclaw, 392k stars), Harness Score (ruvnet/ruflo, 74k stars) and Task Effort Estimator (Donchitos/Claude-Code-Game-Studios, 26k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
microprediction (a GitHub user) maintains it in microprediction/precise, which has 337 GitHub stars. The repository holds 6 skills in this directory. The repository was last updated on October 6, 2026.
Source: microprediction/precise on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.
