review-preflight

review-preflight is a skill for Claude Code, Codex from elevanaltd/HestAI-MCP. It costs 0 tokens per session (1,102 once invoked), scanned A, original, Apache-2.0.

A preparation step for code reviews that gathers a structured summary of the change before detailed judgement begins. It collects information such as changed files, languages, tests, security-sensitive paths, and pull-request status.

In plain words
What is it for?
Use it before pull-request, standalone, or security-focused reviews to map changed files, tests, CI results, and sensitive areas.
Why use it?
It reduces time spent collecting basic context so reviewers can focus on deciding whether the changes are safe and correct.

Skill for Claude CodeCodex

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

Good fit Use it before pull-request, standalone, or security-focused reviews to map changed files, tests, CI results, and sensitive areas.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/elevanaltd/hestai-mcp/review-preflight
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 elevanaltd/HestAI-MCP --skill review-preflight
Clone the repo
git clone --depth 1 https://github.com/elevanaltd/HestAI-MCP

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 review-preflight

README.md
[![agentmods](https://agentmods.dev/badge/skills/elevanaltd/hestai-mcp/review-preflight/github.svg)](https://agentmods.dev/skills/elevanaltd/hestai-mcp/review-preflight)
Your own site
<a href="https://agentmods.dev/skills/elevanaltd/hestai-mcp/review-preflight"><img src="https://agentmods.dev/badge/skills/elevanaltd/hestai-mcp/review-preflight/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 review-preflight

Your own site · 80×15
<a href="https://agentmods.dev/skills/elevanaltd/hestai-mcp/review-preflight"><img src="https://agentmods.dev/badge/skills/elevanaltd/hestai-mcp/review-preflight.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,102 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 $0.00000 $0.01102
Opus 5.5 $0.00000 $0.00441
Sonnet 5.5 $0.00000 $0.00220
Haiku 4.5 $0.00000 $0.00110

Measured 1mo ago against content hash 75740b423b9c, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

review-preflight 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 1mo 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.

src/hestai_mcp/_bundled_hub/library/skills/review-preflight/SKILL.md · 77 lines

How it starts

The opening of the file, as written. The whole thing — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.

===SKILL:REVIEW_PREFLIGHT=== META: TYPE::SKILL VERSION::"1.2.0" STATUS::ACTIVE PURPOSE::"Mechanical prep delegation before review. Collects structured context brief via pal_chat so CRS spends tokens on judgement, not grunt work."

§1::CORE AUTHORITY::ADVISORY[preflight_brief_structure] PHASE::PRE_REVIEW[runs_BEFORE_review-discipline⊕review-prioritization] COMPLEMENTS::[review-discipline,review-prioritization]

§2::PROTOCOL // CRS delegates preflight collection via mcp__pal__chat // CRS runs as subagent (no Task tool) — PAL MCP tools are the delegation path DETECT_CONTEXT::[ PR::"gh_pr_view→has_diff⊕has_CI⊕has_tier", STANDALONE::"file_list_provided→no_PR_metadata", AUDIT::"explicit_audit_scope→security_focus" ] COLLECT::[ CONTEXT_TYPE::PR∨STANDALONE∨AUDIT, FILE_SUMMARY::"files_changed⊕line_delta⊕languages_touched", CI_STATUS::"pipeline_result[PR_only]", TIER::"T0_through_T4_classification[PR_only]", SECURITY_PATHS::"auth∨crypto∨secrets∨permissions∨.env∨tokens", TEST_MAP::"changed_files→existing_test_files[presence_only]", BOT_FINDINGS::"extracted_bot_review_comments[PR_only∧ADVISORY]" ] // BOT_FINDINGS extraction protocol BOT_AUTHORS::[ PRIORITY_1::cubic-dev-ai[bot]<structured_confidence⊕P0-P2_tiers⊕agent_prompts>, PRIORITY_2::github-copilot[bot]<inline_suggestions∧auto_review> ] // LOGIN_NORMALIZATION: GitHub APIs return different login formats for the same // bot accounts. gh pr view --json comments returns logins WITHOUT the [bot] // suffix (e.g., "cubic-dev-ai"), while gh api // repos/{owner}/{repo}/pulls/{pr}/comments preserves the [bot] suffix (e.g., // "cubic-dev-ai[bot]"). Additionally, some bots use legacy login variants // that differ from their canonical name: // - github-copilot[bot] may appear as "Copilot" or "copilot" (no [bot] suffix) // - cubic-dev-ai[bot] may appear as "cubic-bot" // - github-actions is the CI automation account (not a [bot]-suffixed account); // its comments are excluded from gate validation because CI status comments // contain approval-like text that would falsely clear review gates. // The validate_review.py BOT_LOGIN_SET handles this by stripping [bot] from // ADVISORY_BOTS and adding known legacy variant logins. When scanning for bot // comments, match against the normalized set, not the canonical names. BOT_EXTRACT::[ SCAN_ISSUE_COMMENTS::"gh_pr_view--json_comments→filter_by_normalized_BOT_LOGINS[strips_bot_suffix⊕includes_github-actions]", SCAN_REVIEW_COMMENTS::"gh_api_repos/{repo}/pulls/{pr}/comments→filter_by_NORMALIZED_BOT_LOGINS[match_user.login_against:cubic-dev-ai|cubic-bot|github-copilot|Copilot|copilot|github-actions⊕also_match_[bot]_suffix]", CUBIC::"extract_P0_P1_findings⊕confidence_metadata⊕agent_prompt_sections", COPILOT::"extract_inline_suggestions[ADVISORY_context_only]", CLASSIFY::ADVISORY[bot_findings_NEVER_block_merge] ] OUTPUT::STRUCTURED_BRIEF[consumed_by_CRS⊕CE_before_review_begins]

§3::GOVERNANCE DELEGATION::[ TOOL::mcp__pal__chat[or_mcp__pal__clink_for_CLI_providers], PROVIDER_AGNOSTIC::no_model_specification[runtime_selects], FILE_PATHS::pass_absolute_file_paths_parameter[not_inline_code] ] BUDGET::[ BRIEF_ONLY::collect_facts_not_judgements, NO_REVIEW::delegate_NEVER_evaluates_code_quality, CONCISE::brief_fits_in_500_tokens_max ]

§5::ANCHOR_KERNEL TARGET::structured_preflight_brief_with_bot_findings_before_review NEVER::[evaluate_code_quality_in_preflight,specify_model_or_provider,skip_context_detection,produce_findings_or_verdicts,treat_bot_findings_as_blocking] MUST::[detect_review_context_type,collect_file_summary_and_languages,map_security_sensitive_paths,map_changed_files_to_tests,scan_both_issue_comments_AND_review_comments_for_bot_findings,normalize_bot_logins_before_matching,classify_bot_findings_as_ADVISORY,delegate_via_pal_tools] GATE::"Is a structured preflight brief (including bot findings marked ADVISORY) collected via PAL delegation before CRS begins review judgement?"

Read the full file on GitHub · 77 lines

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. 1mo ago First seen · 77 lines · 0 tokens per session scan A 75740b423b9c

Subscribe to this mod's changes

review-preflight is a skill published in the GitHub repository elevanaltd/HestAI-MCP (0 stars, last pushed 11d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 1,102 tokens. 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 2026-09-03.

Related

Other skills, from other repositories

autoreview

Structured code review through the shared OpenClaw agent-skills installation.

openclaw/clawhub · 17 tokens

omh-code-review

This is an OMH code-review workflow skill, projected for Agent Skills hosts (Claude Code, Codex, Cursor, opencode, OpenClaw, pi).

rlaope/oh-my-hermes · 48 tokens

revdiff-plan

Review the last Codex assistant message (plan, analysis, or proposal) with inline annotations in a TUI overlay. Extracts the most recent response from Codex rollout files and opens it in revdiff for review and annotation. Activates on "revdiff-plan", "review plan with revdiff", "annotate plan", "review last response"…

umputun/revdiff · 84 tokens

re0-merge

Review and land an external contribution the way this suite does: gate it against the thesis, land it with the author's credit intact, complete a new skill rather than merging it raw, then approve, credit, and explain before closing. Use when reviewing a pull request, as any collaborator or maintainer, not only the…

LilMGenius/paperthin · 70 tokens

explore-unknowns

Guide the user through a quadrant walk that maps the unknowns of a task — open by listing the known knowns, then work through known unknowns, unknown knowns, and unknown unknowns one stage at a time, ending with a complete four-quadrant map in the user's hands. Use when a request is ambiguous or underspecified, the…

dzhng/skills · 162 tokens

asplos-writing-style

Use when drafting or revising ASPLOS prose — engineering the first two pages that rapid review actually reads, stating the cross-layer insight as one quotable sentence, structuring per-layer mechanism sections, writing bounded claims, and fitting everything into 11 self-contained pages that include figures and…

brycewang-stanford/Awesome-Journal-Skills · 65 tokens