sero-humanize

REVIEW · 59
Registry indexed

Audit or edit Sero Markdown documentation and other product prose to remove AI-writing patterns while preserving technical meaning, product terminology, links, examples, and the repository voice. Use when the user asks to humanize, de-slop, tighten, simplify, rewrite, or audit Se

Verified installs0
Stars19
Version1.0.0
Quality60/100 · Promising
Trust59/100 · Do not auto-install
Audit74/100 · Needs review

Supply asset profile

Research and knowledge work

Deep research, source comparison, literature review, RAG, knowledge search, and reports.

Browse track

Scenario

Research agents

I need my agent to research a topic, compare sources, and produce a concise report.

Agent fit

Claude Code + CLI + Codex

Codex, Claude Code, Cursor, CLI, or custom agents.

Install

Ready

npx skills add sero-labs/sero --skill sero-humanize

Maintenance

fresh

3d since push

Risk

Needs review

Permission surface may require sandboxing

GitHub quality

19

60/100 Quality · 67/100 Trust

Coverage tags

ResearchResearch agentssecurityagent-skill

Review notes

Permission surface may require sandboxing · SKILL.md excerpt is truncated in the provided documentation, but the visible portion is thorough and well-structured.

Agent adoption scorecard

Trust, audit, and install readiness at a glance

These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.

Quality

Promising
60

Useful candidate, but compare it with alternatives before adopting.

Trust

Do not auto-install
59

Trust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.

Audit

Needs review
74

A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.

OpenAgentSkill Trust Score v5

Human review before install

Choose a stronger alternative or inspect the source manually before any install attempt.

CodexClaude CodeCursorOpenAgentSkill CLI

Stars

19 GitHub stars

Repo activity

19 stars, 1 forks

Maintenance

3d since push

License

Apache-2.0

Install

npx skills add sero-labs/sero --skill sero-humanize

Install safety

standard package or runtime install path

Permission surface

secrets or environment access, shell or command execution

Agent outcomes

No agent outcome data yet

Docs

Strong README/SKILL.md context

Risk summary

Review before production

  • SKILL.md excerpt is truncated in the provided documentation, but the visible portion is thorough and well-structured.
  • Low GitHub adoption signal
  • Quality score needs review
  • Permission surface needs review: secrets or environment access, shell or command execution

Install readiness

Install path available

  • Install path is available
  • Repository evidence is available
  • License is declared
  • No Agent Proven outcome evidence yet

Agent-readable metadata

Machine-readable decision data for this skill.

Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.

Open JSON

Suited tasks

  • GitHub automation workflows
  • Claude Code teams
  • builders willing to evaluate younger projects
  • Inspect repository metadata

Suited agents

CodexClaude CodeCursorOpenAgentSkill CLICLI

Install decision

Command
npx skills add sero-labs/sero --skill sero-humanize
Policy
block
Human review
yes

Trust and risk

Trust
59/100
Audit
74/100
Risk level
Needs review

Outcome loop

Endpoint
/api/agent/outcome
Event ID
resolve
Outcomes
5

Install command

npx skills add sero-labs/sero --skill sero-humanize

Do not use when

  • teams that need a vendor-supported SLA
  • production agents without a repository review
  • Low GitHub adoption signal
  • SKILL.md excerpt is truncated in the provided documentation, but the visible portion is thorough and well-structured.
  • High-risk permission hints: Shell or command execution, Secrets or environment access

Agent safety v2

34/100 · Avoid automatic install

Blocked for auto-installblock

This skill should not be selected by an agent without explicit human security review.

Do not auto-install. Inspect the source, dependencies, and permission surface first.

Resolve via API

high

Shell or command execution

Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.

medium

Network access

Skill likely fetches remote pages, APIs, repositories, or external services.

medium

Filesystem access

Skill may read or write project files, documents, generated artifacts, or local workspace state.

high

Secrets or environment access

Skill metadata references credentials, tokens, environment variables, or secret-bearing workflows.

  • High-risk permission hints: Shell or command execution, Secrets or environment access
  • Permission surface may require sandboxing

Install targets

Install this skill in your agent workflow

Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.

skill install

OpenAgentSkill CLI

Resolve policy, run the source installer safely, and report a verified install receipt.

$ npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install sero-labs-sero-humanize

Agent resolve plan

Let an agent verify fit before installing.

The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.

Open text plan

Agent should check

  • Task fit and alternatives from Resolve API.
  • Audit score, trust score, and safety policy warnings.
  • Install target compatibility for Codex, Claude Code, Cursor, or CLI.

Copy prompt

Task: Use sero-humanize in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20sero-humanize%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/sero-labs-sero-humanize/install
Install command: npx skills add sero-labs/sero --skill sero-humanize
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.

Agent handoff

Give an agent the install path, not another directory page.

Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.

Open install API

Agent prompt

Use sero-humanize for this task. Review https://www.openagentskill.com/api/skills/sero-labs-sero-humanize/install, then install with: npx skills add sero-labs/sero --skill sero-humanize

Registry metadata

Agent-readable profile for automatic skill selection.

This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.

Open manifest

Agent fit

61/100

GitHub automation

Platforms

Claude Code

Audit report

Needs review · 74/100

A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.

View audit reportView eval report

Agent decision cockpit

Fallback candidate for GitHub automation

Prototype with this skill first; keep a fallback candidate ready.

61
Readiness
Prototype
Stage

Role in stack

Fallback candidate

Primary fit

GitHub automation

Trust label

Prototype first

Install path

Command ready

Use when

  • GitHub automation workflows
  • Claude Code teams
  • builders willing to evaluate younger projects

Evidence

  • recent repository activity
  • install command or GitHub repo available
  • 60/100 quality profile
  • 6 OpenAgentSkill engagement events

review first

  • Low GitHub adoption signal
  • SKILL.md excerpt is truncated in the provided documentation, but the visible portion is thorough and well-structured.

Implementation path

  1. 1Install it in a sandbox agent and run one GitHub automation task end to end.
  2. 2Compare output quality, latency, and failure behavior against at least one alternative.
  3. 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.

Trust profile

Do not auto-install

Trust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.

59
OpenAgentSkill Trust Score

GitHub adoption

FIX

19 GitHub stars

Stars/forks activity

FIX

19 stars, 1 forks; issue activity unavailable in current metadata

Recent maintenance

PASS

3d since push

License clarity

PASS

Apache-2.0

Good signals

  • AI review approved
  • Install path is available
  • Repository evidence is available
  • Recently maintained repository
  • Install command has no obvious high-risk pattern
  • Outcome loop is ready but needs first real agent run

Review before install

  • SKILL.md excerpt is truncated in the provided documentation, but the visible portion is thorough and well-structured.
  • Low GitHub adoption signal
  • Quality score needs review
  • Permission surface needs review: secrets or environment access, shell or command execution
  • GitHub adoption: 19 GitHub stars
  • Stars/forks activity: 19 stars, 1 forks; issue activity unavailable in current metadata
  • Permission surface: secrets or environment access, shell or command execution
  • No real agent outcome reports yet
  • Human review required before unattended installation

Recommended action

Choose a stronger alternative or inspect the source manually before any install attempt.

Quality profile

Promising candidate for agent workflows

Useful candidate, but compare it with alternatives before adopting.

60
GitHub stars
19
Freshness
3d ago
Install ready
Yes
License
Apache-2.0
Review before install: Low GitHub adoption signal · SKILL.md excerpt is truncated in the provided documentation, but the visible portion is thorough and well-structured.

Workflow fit

Use this skill in these scenarios

Workflow fit

Add it to a complete workflow

Alternative shortlist

Compare before you install

Similar skills that may fit this task.

Compare all

Overview

--- name: sero-humanize description: | Audit or edit Sero Markdown documentation and other product prose to remove AI-writing patterns while preserving technical meaning, product terminology, links, examples, and the repository voice. Use when the user asks to humanize, de-slop, tighten, simplify, rewrite, or audit Sero documentation, README text, UI copy, release notes, plans, or specifications for AI tells. Also use when prose needs ASD-STE100 Simplified Technical English. Do not use for code review or for creative and promotional writing. ---

# Sero Humanize

Make Sero prose direct, specific, and useful. Human writing in technical documentation does not need personality. It needs clear decisions, concrete facts, and respect for the reader's time.

## Follow the requested mode

- For an audit or review, report the material patterns and do not edit files. - For an edit, rewrite the named files in place. - For a new document, apply these rules while drafting it. - If the request does not specify a mode, infer it from the requested action. Do not turn a request to assess prose into permission to change it.

## Establish the voice and preservation set

Before editing:

1. Read every file in scope in full. 2. Read the nearest repository instructions that apply to those files. 3. Use adjacent, clearly human-edited Sero documentation as the voice sample when the named files do not establish a consistent voice. 4. Record what must not change: - technical meaning and product behaviour; - product names, canonical terms, and exact UI labels; - commands, code, file paths, numbers, limits, and factual claims; - the documentation type, useful narrative flow, and balance between prose, lists, tables, examples, and callouts; - frontmatter, anchors, link targets, image paths, and screenshot order; - the purpose and placement of each image, diagram, and other media asset; - quotations and user input examples, unless the user asks to edit them.

Identify the intended reader. Unless the page states otherwise, assume the reader knows neither Sero nor the feature. Do not assume that simpler grammar fixes an explanation that requires missing product knowledge.

Do not add a fact to make a sentence more vivid. Verify a doubtful claim from the repository or leave it unchanged and report the doubt.

## Audit structure before wording

Look for clusters and repeated patterns. Do not treat one punctuation mark or one common word as proof of AI writing.

Prioritize these defects:

- Meta narration that announces the next explanation instead of giving it. - Repeated tutorial staging such as "what you are about to learn" and "what you have learned." - Fixed enumerations such as "three things are worth noticing" when a direct heading or short list is clearer. - Several paragraphs that can change order without changing the argument. - A heading followed by a sentence that only repeats the heading. - A conclusion that repeats the introduction without adding an action or fact. - Repeated summaries of the same screen, process, or result. - Forced contrasts such as "not only X, but Y" or "not X; rather Y." - Groups of three used for rhythm instead of meaning. - Mechanical bold lead-ins, excessive inline bold, or lists that should be short prose. - Promotional adjectives, vague importance claims, and unsupported praise. - Vague actors, passive constructions, filler, stacked hedges, and abstract nouns where an action is available. - Synonym cycling for one product concept. Repeat the canonical term. - Long sentences that mix instructions, exceptions, and background. - Em dashes used repeatedly to join thoughts that need separate sentences. - Headings that narrate the demo or expose implementation language instead of naming the reader's task, such as "The finish" or "Answer the gate." - Examples that depend on an unexplained demo domain and therefore do not help the reader understand the feature. - Tutorials that start using the product before they give prerequisites, sample data, expected starting state, or required sign-ins. - Result sections that recite one captured run instead of telling the reader what to inspect and verify.

Keep useful structure. A list, summary, warning, question heading, or em dash is not a defect by itself.

Do not normalize a page or site to one format. Humanize the defective passages, not every paragraph. If a page already explains a concept well in prose, keep it as prose.

## Rewrite for Sero documentation

Apply ASD-STE100 Simplified Technical English where it fits the material:

- Put the action or answer first. - Use active voice when the actor matters. - Give one main instruction per sentence. - Put a condition before the action when the reader must know it first. - Prefer common, precise words over formal or promotional alternatives. - Use the same term for the same thing. - Keep paragraphs focused on one subject. - Keep necessary limits, cautions, and exceptions close to the action. - Use contractions only when the established local voice requires them. - Keep exact UI text in bold when the documentation uses bold for controls. - Keep code identifiers and paths in code formatting. - Retain a summary only when it helps the reader decide or act.

Use lists only when the content is naturally a sequence, set of choices, checklist, or compact reference. Do not:

- convert explanatory prose into bullet points only to make it shorter; - turn each sentence or paragraph into a list item; - replace transitions and reasoning with disconnected bullets; - use repeated lists where a short paragraph gives the reader necessary context; or - make several pages share the same mechanical list structure.

After the sentence pass, read the page as a whole. If lists now dominate a page that previously used useful prose, restore the prose. Clear technical writing needs connected explanation as well as scannable reference material.

For an overview page:

- Explain the feature in familiar words before using its product terms. - State what the user gives Sero, what Sero does, and what the user reviews. - When comparing features, give one plain decision rule. Use examples that a reader can understand without knowing the tutorial repository or a specialist software domain.

For a tutorial:

- Put setup before the first product action. Include required software, accounts, sign-ins, repository or sample-data setup, and a command or visible result that confirms the expected starting state. - Prefer a stable sample repository over instructions that ask an agent to generate approximate sample data. Verify the repository contents and commands before documenting them. - Use task-based headings such as "Review the plan," "Change the plan," and "Check the result." A heading must describe the full purpose of its section; do not narrow a general control to one example case. - End with checks the reader can perform. Do not use a captured run's cost, duration, names, or outcome as a substitute for verification instructions.

For feature language:

- Use the visible object name: icon, button, tab, question, or approval request. Do not call an icon a mark or expose internal terms such as gate, fan-out, or feedback route when plain behaviour is enough. - Keep exact UI labels unchanged, but explain them with common words. - Put high-value quality-of-life features where readers will find them. Give them enough space to explain when the control appears, how to use it, what it changes, and what remains under user control.

Compress or merge only the passages that contain a verified structural defect. Keep useful depth, examples, transitions, and paragraph structure. A shorter page is not automatically a better page.

Do not manufacture a human voice with:

- anecdotes, opinions, jokes, sensory details, or personal asides; - fragments, one-word sentences, or dramatic punch lines; - arbitrary sentence-length variation; - unusual synonyms chosen only to make wording less predictable; - metaphors that replace a precise technical explanation; - deliberate imperfections or tangents; - an invented AI probability or numerical slop score.

## Preserve Markdown and product accuracy

- Do not change fenced code, commands, URLs, link targets, image targets, or frontmatter unless the request requires it. - Do not rename a heading if another page links to its generated anchor without updating that link. - Do not change a UI label to improve prose. Rewrite the surrounding sentence. - Do not remove repetition that is required for independent reference sections. - Do not convert a walkthrough into reference documentation, or reference documentation into a narrative tutorial, without user approval. - Do not infer product behaviour from the prose alone when the edit changes a technical claim. Check the implementation or an authoritative reference. - Treat contradictions between prose, screenshots, capture metadata, sample repositories, and implementation as accuracy defects. Resolve them from the authoritative source instead of rewriting around them. - When a page title changes, update the sidebar, index, related-page labels, and in-scope links that display the old title.

## Preserve images and other media

Treat every existing image, diagram, video, and asset as preserved content. Humanizing prose does not authorize media removal or replacement.

- Do not delete an asset, remove its reference, change its order, or replace it unless the user explicitly approves that action. - Do not use "task value," brevity, a stale appearance, or a text explanation as automatic reasons to remove an image. - Do not bulk-delete assets during a prose revision. - If an image is stale, private, inaccurate, decorative, or duplicated, report the issue and propose one action: keep, recapture, move, or remove. Wait for approval before changing it. - If an image exposes a credential or other active secret, stop publication and report it immediately. Do not silently make a wider set of image changes. - When a replacement is approved, capture or obtain the replacement before removing the current asset. Preserve the route and layout while replacement work is pending. - Check non-doc consumers before changing an asset. README files, homepages, package pages, and other applications can import docs-site images directly.

A decision not to add a new screenshot is not permission to remove an existing screenshot.

## Control the size of the rewrite

For a large documentation set, work in reviewed vertical slices. Complete and review one representative page before applying the approach to the rest of a slice. Do not perform a site-wide structural rewrite from an audit summary.

Pause and ask for approval when the work would:

- change the dominant format of a page, such as prose to lists; - remove substantial explanation, examples, or media; - merge, tombstone, redirect, or delete a page; - change many pages through the same structural template; or - produce a much larger diff than the factual and prose defects require.

When several agents contribute, give them the same preservation set and require a central review of format balance and media changes before integration.

## Use a two-pass edit

### Pass 1: structure

Remove redundant framing, merge repeated explanations, order information by the reader's task, and keep prerequisites before dependent actions. Give prominent placement to features that materially improve repeated use; do not give every feature equal weight merely because the source page did.

Keep the smallest effective structural change. Do not rewrite a complete page when a heading, transition, or paragraph edit fixes the defect.

### Pass 2: sentences

Remove filler and AI mannerisms. Simplify grammar. Keep terminology and facts stable. Read the result as technical documentation, not as marketing copy.

Then compare the result with th

Technical details

Version
1.0.0
License
Apache-2.0
Last updated
Aug 19, 2026
Published
Aug 19, 2026

Decision snapshot

Fallback candidate

61
Ready
Prototype
Stage

recent repository activity

Audit

Install review

Install and adoption review

74
Needs review
Security
74/100
Maintenance
100/100
Install
92/100
Open full auditView eval report

Agent-proven evidence

Agent-proven evidence

Outcome reports after resolve, review, install, and one narrow run.

0
Proven
Needs first agent runAuto-install: review firstLast: Unknown
Success rate
Recent failure
Outcomes
0
Output quality
Failed
0
Not relevant
0
Installs
0
Risk blocked
0
Setup needed
0
Production
0

No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.

Install

Add to agent workflow

Free and open source. Review the report before installing into production agents.

Growth loop

Share kit

X

Scenario-led draft for sero-humanize, ready for a manual X post.

Curator note
A practical pick for design or creative work:

sero-humanize: Audit or edit Sero Markdown documentation and other product prose to remove AI-writing patterns while preserving technical...

19 stars

https://www.openagentskill.com/skills/sero-labs-sero-humanize?ref=x
Open X draft
Optional reply with install command
Listing + install path for sero-humanize:
https://www.openagentskill.com/skills/sero-labs-sero-humanize?ref=x

Install: npx skills add sero-labs/sero --skill sero-humanize

Listing source

Registry indexed

Claimable

This listing was indexed from public sources and is not marked official until a maintainer claim is approved.

Creator
sero-labs
Indexed by
OpenAgentSkill community index

Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.

Claim this skill

Owner claim

Claim this skill listing

This Registry indexed listing is attributed to sero-labs but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.

Creator backlink kit

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Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.

[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/sero-labs-sero-humanize?metric=listed&label=Listed)](https://www.openagentskill.com/skills/sero-labs-sero-humanize)
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Author

S

sero-labs

@sero-labs

Platform fit

Health signals

GitHub stars
19
Quality score
33/100
Last GitHub push
Aug 19, 2026
Framework hints
Unknown
OpenAgentSkill views
6
Install copies
0
Outbound clicks
0

Community signal

Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.

Trust & safety

Do not auto-install

59
  • GitHub adoption19 GitHub starsFIX
  • Stars/forks activity19 stars, 1 forks; issue activity unavailable in current metadataFIX
  • Recent maintenance3d since pushPASS
  • License clarityApache-2.0PASS
  • README/SKILL.md completenessMetadata includes enough usage and workflow contextPASS
  • Dependency/runtime riskcredential or environment accessINFO