Raytsystem Research
romarayt/raytsystem-public-os
Perform bounded source research for raytsystem and return provenance-rich evidence proposals without canonical writes.
Use only when the user explicitly invokes $audit-onboarding-proposal.
$ npx skills add hoangnb24/repository-harness --skill audit-onboarding-proposal -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install hoangnb24/repository-harness audit-onboarding-proposal --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/hoangnb24/repository-harness.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/audit-onboarding-proposal .claude/skills/audit-onboarding-proposal && 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 "audit-onboarding-proposal" agent skill from https://github.com/hoangnb24/repository-harness/tree/main/.agents/skills/audit-onboarding-proposal into .claude/skills/audit-onboarding-proposal/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "audit-onboarding-proposal", 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/hoangnb24/repository-harness/tree/main/.agents/skills/audit-onboarding-proposalType 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 hoangnb24/repository-harness --skill audit-onboarding-proposal -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install hoangnb24/repository-harness audit-onboarding-proposal --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hoangnb24/repository-harness.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/audit-onboarding-proposal .agents/skills/audit-onboarding-proposal && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "audit-onboarding-proposal" agent skill from https://github.com/hoangnb24/repository-harness/tree/main/.agents/skills/audit-onboarding-proposal into .agents/skills/audit-onboarding-proposal/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "audit-onboarding-proposal", 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 hoangnb24/repository-harness --skill audit-onboarding-proposal -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install hoangnb24/repository-harness audit-onboarding-proposal --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hoangnb24/repository-harness.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/audit-onboarding-proposal .cursor/skills/audit-onboarding-proposal && 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 "audit-onboarding-proposal" agent skill from https://github.com/hoangnb24/repository-harness/tree/main/.agents/skills/audit-onboarding-proposal into .cursor/skills/audit-onboarding-proposal/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "audit-onboarding-proposal", 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/hoangnb24/repository-harness.git --path .agents/skills/audit-onboarding-proposal--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 hoangnb24/repository-harness --skill audit-onboarding-proposal -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install hoangnb24/repository-harness audit-onboarding-proposal --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hoangnb24/repository-harness.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/audit-onboarding-proposal .gemini/skills/audit-onboarding-proposal && 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 "audit-onboarding-proposal" agent skill from https://github.com/hoangnb24/repository-harness/tree/main/.agents/skills/audit-onboarding-proposal into .gemini/skills/audit-onboarding-proposal/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "audit-onboarding-proposal", 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 hoangnb24/repository-harness audit-onboarding-proposalInstalls 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 hoangnb24/repository-harness --skill audit-onboarding-proposal -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/hoangnb24/repository-harness.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/audit-onboarding-proposal .github/skills/audit-onboarding-proposal && 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 "audit-onboarding-proposal" agent skill from https://github.com/hoangnb24/repository-harness/tree/main/.agents/skills/audit-onboarding-proposal into .github/skills/audit-onboarding-proposal/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "audit-onboarding-proposal", 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 hoangnb24/repository-harness --skill audit-onboarding-proposal -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install hoangnb24/repository-harness audit-onboarding-proposal --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hoangnb24/repository-harness.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/audit-onboarding-proposal .opencode/skills/audit-onboarding-proposal && 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 "audit-onboarding-proposal" agent skill from https://github.com/hoangnb24/repository-harness/tree/main/.agents/skills/audit-onboarding-proposal into .opencode/skills/audit-onboarding-proposal/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "audit-onboarding-proposal", 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.
audit-onboarding-proposalUse only when the user explicitly invokes $audit-onboarding-proposal.
Audit Onboarding Proposal is an agent skill from hoangnb24/repository-harness. Use only when the user explicitly invokes $audit-onboarding-proposal. Independently audit an onboarding transcript and exact evidence-backed proposals. Remain read-only and verify claims against pinned repository evidence rather than trusting the producer.
Its SKILL.md is about 4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including scripts (for example `agents/openai.yaml` and `scripts/validate_evidence_capsule.py`).
It sits in Sales & Support, covering Proposals and quotes and Fact-checking and source verification. The repository describes itself as: Turn any repo into an agent-ready workspace for Claude Code, Codex, Cursor, and other coding agents. The licence is MIT.
5 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 485fd40. 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.
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python3nodeFrom 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.
Audit Onboarding Proposal loads about 4k tokens when it runs. Until then it costs about 71 tokens; SKILL.md has 2,086 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); the scripts in this folder are not scanned.
The full file from hoangnb24/repository-harness at commit 485fd40, republished under its MIT licence (© hoangnb24). 2,086 words, ~3,992 tokens.
.claude/skills/audit-onboarding-proposal/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.Audit the producer, not the producer's story about itself. Reconstruct the run from raw evidence, verify every proposed clause against repository authority, and return hunk-level apply or no-apply decisions.
python3 -c/node -e programs, stdin pipes, or
ordinary read-only commands instead.Require or discover:
If the transcript does not identify its worktree or revision, mark causal eligibility Invalid rather than guessing.
Use patch-admissibility mode when the request is only whether one or more exact
hunks from a valid onboarding-evidence-capsule/v2 are safe to present for
approval. Authenticated v1 transcripts remain eligible as legacy evidence but
do not receive repository-aware hash verification. Require the authenticated
transcript, its expected digest, the tested revision, and explicit hunk IDs. Do
not infer the requested hunk set.
Run the evidence-capsule validator, then inspect only material needed to decide the requested hunks. For each requested hunk:
PATCH_APPLY only if every required check passes.Do not reconstruct the complete resource ledger, operational path, producer
no-mutation vector, or five-gate score unless one is directly necessary to
decide a requested clause. State Producer gates: not recomputed; patch-admissibility audit only. This mode decides whether displayed wording is
evidence-backed; it does not certify onboarding quality, producer safety, or
permission to mutate the consumer. A missing capsule, invalid capsule, missing
hunk ID, source mismatch, incomplete source chain, omitted worksheet cell, or
unresolved counterexample forces PATCH_NO_APPLY for the affected hunk.
End with one PATCH_APPLY or PATCH_NO_APPLY disposition per requested hunk,
then PATCH_ADMISSIBILITY_COMPLETE. Do not emit the full-audit
AUDIT_COMPLETE marker in this mode.
Use corrected-reissue mode only when an authenticated producer transcript already contains the evidence for a previously displayed hunk and the producer or coordinator has issued one exact corrected replacement for that same hunk. Require the original transcript path and digest, tested revision, exact reissue location or complete text, and the reissue digest when available.
Authenticate the original transcript, but reconstruct only the evidence needed
for the reissued hunk. Do not rescore unrelated maps, proposals, or hunks, and
do not repeat the five-gate producer score. State Producer gates: not recomputed; corrected-reissue audit only. A reissue audit cannot rehabilitate
the original bundle or authorize any undisplayed text.
Run the complete Patch Verification Worksheet and counterexample pass for the
reissued hunk. Compare its destination boundary and exact changed text against
the tested repository and every claimed canonical source. Verify all changed
clauses independently even when the correction is described as verbatim. End
with REISSUE_APPLY or REISSUE_NO_APPLY, followed by AUDIT_COMPLETE.
When the tested producer skill contains
ONBOARDING_EVIDENCE_BUNDLE_V2, the raw transcript must contain one complete
machine-emitted bundle before task completion. The producer's final assistant
message references its digest and hunk IDs rather than duplicating its bytes.
Legacy producer revisions may instead include the marked JSON capsule and
marked diff hunks in the completed assistant message. After authenticating the
raw transcript, run:
python3 .agents/skills/audit-onboarding-proposal/scripts/validate_evidence_capsule.py --transcript <raw-session.jsonl> --expected-transcript-sha256 <sha256> --repository <tested-worktree>The validator is read-only. It verifies capsule structure, referential
integrity, boundary-result hash invariants, pinned producer/source blobs,
displayed patch hashes, exact patch applicability, and whole-destination
before/after hashes. For a machine bundle it also reports
evidence_source=machine_tool_output and verifies the exact inner-bundle
digest. Treat a missing, truncated, or invalid required bundle/capsule as a
gate-3 failure and return NO APPLY for its unverified hunks. V1 capsules
remain structurally valid legacy evidence but do not receive repository-aware
source or destination verification; full semantic audit remains required.
A v2 capsule with empty claims and hunks records no proposed backfill. Verify its authentication and boundary evidence; it supplies no patch to admit or approve and does not establish that the repository has no remaining gaps.
A valid capsule is an authenticated index, not evidence. Independently retrieve every cited source from its pinned revision, hash the exact cited line range, verify each atomic clause, and scan the destination and adjacent sources for omissions or counterexamples. Use the capsule to avoid rereading unrelated tool results; never use it to skip repository completeness, boundary, or counterexample checks relevant to the proposed hunks.
Use this complete workflow only for a full onboarding-quality audit. The two narrow modes above use their stated subset and must not silently expand into a full producer rescore.
Verify the transcript hash. Extract, in order:
Score the final answer, but use intermediate tool evidence to test it. Do not credit a final claim merely because the producer stated it.
Compare initial and final evidence separately for:
At the tested revision, read every root and nested ignore file applicable to the inspected paths. Expand its relevant literal paths and patterns into an independent checklist, then compare that checklist with the producer's initial capture. A path that was first checked later cannot receive a pre/post pass. A producer summary saying "ignored state passed" is not evidence that every applicable pattern was baselined.
Use Pass, Fail, or Unknown for each component. Compute the no-mutation gate conjunctively: every required component must pass; one Unknown makes the result gate fail. Do not convert "no mutating command was seen" into "external state was unchanged."
Build an independent inventory from request bodies, environment merges, configuration, Compose manifests, schemas, serializers, and logging code. Then compare it with the producer ledger.
Require one row per:
Do not accept combined identifiers, logical names presented as runtime names, optional fields presented as universal, or process-wide metrics presented as request/instance evidence.
Reconstruct actual control-flow order rather than a generic conceptual order. Verify prerequisites, startup, setup/migration, readiness, every real interface exercise, evidence, successful completion, no-start modes, requested teardown, and every failure path relevant to cleanup.
For every row require explicit values for command/result, classification and source, write at that stage, owner, host/container ports, evidence/correlation, cleanup, and unknowns. Verify full causal chains for persistence, provider calls, logging, and runtime effects; an entrypoint alone is not sufficient.
Distinguish:
Require all six proposal fields: prevented failure, evidence, destination, factual content, unknowns, and replay proof.
Before deciding any hunk, produce a Patch Verification Worksheet with one row per hunk and these columns:
| Hunk | Destination and exact boundary | Structural comparison | Atomic changed clauses | Complete source chain | Conditions preserved | Preliminary disposition |
|---|
Every cell is mandatory. Structural comparison must identify every heading,
marker, and unchanged boundary line and report either byte-for-byte equality
with the claimed source or the first differing line. Atomic changed clauses
must split conjunctions and multi-sentence paragraphs into separately numbered
claims. Conditions preserved must name every source branch, guard, fallback,
and failure-order qualifier relevant to those claims; none is allowed only
after explicitly checking for them.
Use non-materializing comparisons where possible. For a managed-marker hunk, extract the complete proposed marker block from the authenticated final answer and compare it with the complete checksum-verified base marker block. Do not compare only the body or visually sample the beginning and end. If extraction cannot be proven complete, the hunk is NO APPLY.
For each displayed hunk:
For managed-marker replacement, compare the full displayed replacement byte-for-byte with the checksum-verified base content. A missing heading or line makes the hunk NO APPLY.
After drafting the worksheet, run a separate counterexample pass. Try to
disprove each preliminary APPLY by checking, in this order:
before, after, successful, complete, or finally wording that does
not match the exact control-flow signal; andRecord Counterexample found: none or the exact counterexample for every
hunk. An omitted worksheet cell, omitted counterexample result, incomplete
structural extraction, or unverified atomic clause forces NO APPLY; do not
use reviewer confidence to fill the gap.
Return APPLY, NO APPLY, or SPLIT AND REISSUE per hunk. Never approve an entire bundle because most sentences are correct.
Apply this section only in full onboarding-quality audit mode.
Return this exact five-gate vector:
Then separately return Output correctness: Pass|Fail. Output correctness may
pass with gate 5 failed only when the producer accurately reported an
environment-caused Unknown and did not overclaim state equivalence.
Apply this complete report shape only in full onboarding-quality audit mode.
Return:
End with an explicit AUDIT_COMPLETE marker. Do not apply or commit any patch.
The audit report is structurally incomplete unless every proposed hunk appears
in both the worksheet and counterexample pass. When structurally incomplete,
set Output correctness: Fail and return NO APPLY for every unverified
hunk even if its wording appears plausible.
© hoangnb24, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 2 other files (scripts) in .agents/skills/audit-onboarding-proposal of hoangnb24/repository-harness.
Open the folder on GitHubat commit 485fd40
Audit Onboarding Proposal 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 |
|---|---|---|---|---|---|---|
| Audit Onboarding Proposal this skillhoangnb24/repository-harness | 1.2k | — | ~4k | Automated safety check: Pass | MIT | |
| Raytsystem Researchromarayt/raytsystem-public-os | 149 | — | ~557 | Automated safety check: Pass | Apache-2.0 | |
| Doc Coauthoringaws-samples/sample-strands-agent-with-agentcore | 195 | 40 repos | ~3.2k | Automated safety check: Pass | MIT | |
| No Negative EchoLB623/no-negative-echo | 900 | — | ~965 | Automated safety check: Pass | MIT | |
| GEO Service Proposal Generatorzubair-trabzada/geo-seo-claude | 11k | — | ~3k | Automated safety check: Notes | MIT | |
| Architectural ProposalsFritzAndFriends/SharpSite | 145 | 2 repos | ~1.6k | Automated safety check: Pass | MIT |
romarayt/raytsystem-public-os
Perform bounded source research for raytsystem and return provenance-rich evidence proposals without canonical writes.
aws-samples/sample-strands-agent-with-agentcore
Guide users through a structured workflow for co-authoring documentation.
LB623/no-negative-echo
Prevent 此地无银三百两式 residue: finalize artifacts without echoing rejected session-only alternatives into labels, metadata, commits, PRs, or handoffs.
zubair-trabzada/geo-seo-claude
Builds a client-ready AI-search-optimization proposal from an existing GEO audit, with pricing tiers, an ROI estimate and a markdown document ready to send.
FritzAndFriends/SharpSite
How to write comprehensive architectural proposals that drive alignment before code is written
zubair-trabzada/ai-legal-claude
Generates specific counter-proposals for every unfavorable clause, with replacement language, negotiation talking points, and a ready-to-send email template
hoangnb24/repository-harness
Use only when the user explicitly invokes $onboard-repository.
hoangnb24/repository-harness
Use only when the user explicitly invokes $engineering-wisdom.
hoangnb24/repository-harness
Use only when the user explicitly invokes $improve-harness. An agent skill from hoangnb24/repository-harness.
hoangnb24/repository-harness
Use only when the user explicitly invokes $encode-invariant.
Categories
Use only when the user explicitly invokes $audit-onboarding-proposal. Audit Onboarding Proposal is an agent skill from hoangnb24/repository-harness. Use only when the user explicitly invokes $audit-onboarding-proposal.
Audit Onboarding Proposal fits situations like: explicitly invokes $audit-onboarding-proposal; tasks that involve Proposals and quotes; tasks that involve Fact-checking and source verification.
Run `npx skills add hoangnb24/repository-harness --skill audit-onboarding-proposal -a claude-code`. Or copy the skill folder (.agents/skills/audit-onboarding-proposal in hoangnb24/repository-harness) into .claude/skills/audit-onboarding-proposal in your project. Claude Code loads it when a task matches its description.
Run `npx skills add hoangnb24/repository-harness --skill audit-onboarding-proposal -a codex`. Or copy the skill folder (.agents/skills/audit-onboarding-proposal in hoangnb24/repository-harness) into .agents/skills/audit-onboarding-proposal 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 hoangnb24/repository-harness --skill audit-onboarding-proposal -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/audit-onboarding-proposal, .gemini/skills/audit-onboarding-proposal, .github/skills/audit-onboarding-proposal and .opencode/skills/audit-onboarding-proposal in your project.
Going by SKILL.md and its folder, Audit Onboarding Proposal needs Python for the scripts in its folder and the command-line tools its instructions call (python3 and node). 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
Audit Onboarding Proposal is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 4k tokens (SKILL.md is roughly 16k 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 Audit Onboarding Proposal: Raytsystem Research (romarayt/raytsystem-public-os, 149 stars), Doc Coauthoring (aws-samples/sample-strands-agent-with-agentcore, 195 stars), No Negative Echo (LB623/no-negative-echo, 900 stars) and GEO Service Proposal Generator (zubair-trabzada/geo-seo-claude, 11k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
hoangnb24 (a GitHub user) maintains it in hoangnb24/repository-harness, which has 1,243 GitHub stars. The repository holds 5 skills in this directory. The repository was last updated on October 4, 2026.
Source: hoangnb24/repository-harness on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.