File Uploads
davila7/claude-code-templates
Expert at handling file uploads and cloud storage. An agent skill from davila7/claude-code-templates.
Find a local Claude Code or Codex session, open the BenchFlow trajectory viewer, and submit it after the user reviews it.
$ npx skills add benchflow-ai/benchflow --skill benchflow-traj-upload -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install benchflow-ai/benchflow benchflow-traj-upload --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/benchflow-ai/benchflow.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/benchflow-traj-upload .claude/skills/benchflow-traj-upload && 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 "benchflow-traj-upload" agent skill from https://github.com/benchflow-ai/benchflow/tree/main/.agents/skills/benchflow-traj-upload into .claude/skills/benchflow-traj-upload/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "benchflow-traj-upload", 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/benchflow-ai/benchflow/tree/main/.agents/skills/benchflow-traj-uploadType 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 benchflow-ai/benchflow --skill benchflow-traj-upload -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install benchflow-ai/benchflow benchflow-traj-upload --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/benchflow-ai/benchflow.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/benchflow-traj-upload .agents/skills/benchflow-traj-upload && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "benchflow-traj-upload" agent skill from https://github.com/benchflow-ai/benchflow/tree/main/.agents/skills/benchflow-traj-upload into .agents/skills/benchflow-traj-upload/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "benchflow-traj-upload", 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 benchflow-ai/benchflow --skill benchflow-traj-upload -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install benchflow-ai/benchflow benchflow-traj-upload --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/benchflow-ai/benchflow.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/benchflow-traj-upload .cursor/skills/benchflow-traj-upload && 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 "benchflow-traj-upload" agent skill from https://github.com/benchflow-ai/benchflow/tree/main/.agents/skills/benchflow-traj-upload into .cursor/skills/benchflow-traj-upload/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "benchflow-traj-upload", 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/benchflow-ai/benchflow.git --path .agents/skills/benchflow-traj-upload--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 benchflow-ai/benchflow --skill benchflow-traj-upload -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install benchflow-ai/benchflow benchflow-traj-upload --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/benchflow-ai/benchflow.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/benchflow-traj-upload .gemini/skills/benchflow-traj-upload && 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 "benchflow-traj-upload" agent skill from https://github.com/benchflow-ai/benchflow/tree/main/.agents/skills/benchflow-traj-upload into .gemini/skills/benchflow-traj-upload/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "benchflow-traj-upload", 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 benchflow-ai/benchflow benchflow-traj-uploadInstalls 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 benchflow-ai/benchflow --skill benchflow-traj-upload -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/benchflow-ai/benchflow.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/benchflow-traj-upload .github/skills/benchflow-traj-upload && 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 "benchflow-traj-upload" agent skill from https://github.com/benchflow-ai/benchflow/tree/main/.agents/skills/benchflow-traj-upload into .github/skills/benchflow-traj-upload/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "benchflow-traj-upload", 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 benchflow-ai/benchflow --skill benchflow-traj-upload -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install benchflow-ai/benchflow benchflow-traj-upload --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/benchflow-ai/benchflow.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/benchflow-traj-upload .opencode/skills/benchflow-traj-upload && 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 "benchflow-traj-upload" agent skill from https://github.com/benchflow-ai/benchflow/tree/main/.agents/skills/benchflow-traj-upload into .opencode/skills/benchflow-traj-upload/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "benchflow-traj-upload", 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.
benchflow-traj-uploadFind a local Claude Code or Codex session, open the BenchFlow trajectory viewer, and submit it after the user reviews it.
Benchflow Traj Upload is an agent skill from benchflow-ai/benchflow. Find a local Claude Code or Codex session, open the BenchFlow trajectory viewer, and submit it after the user reviews it. Use this skill whenever someone pastes a BenchFlow eval prize line, wants to submit / share / contribute / upload a trajectory, set up traj upload, view a session, or pick a session to send. Also use it when they mention the eval prize, benchflow-traj-upload, or "copy this to your agent".
Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `evals/evals.json`).
The repository describes itself as: Research infra for creating RL environments, post-training, and evals. The licence is Apache-2.0.
7 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit e965eee. It shows what the files ask for, not the result of running them.
Pre-approves these tools, so the agent can use them without asking each time:
ReadBashFrom allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
uvopencodeFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use uv, which can reach the network depending on how they are called.
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.
Benchflow Traj Upload loads about 1.9k tokens when it runs. Until then it costs about 108 tokens; SKILL.md has 965 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 noted patterns worth knowing about, such as sudo or a known installer.
allowed-tools: Read, BashAutomated 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 benchflow-ai/benchflow at commit e965eee, republished under its Apache-2.0 licence (© benchflow-ai). 965 words, ~1,883 tokens.
.claude/skills/benchflow-traj-upload/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.The human copied a line into this chat so you would do the work. They should not run BenchFlow commands. You find a local session, open the viewer, wait until they like it, then you upload.
Do not print broker URLs, Azure blob URLs, or a "run this yourself" command. Those leak private inbox paths and turn a paste-to-agent flow back into a CLI.
For operating, testing, or debugging the upload pipeline itself (dry runs,
manifests, promotion checks), use benchflow-traj-upload-ops instead.
1. setup → ensure the latest benchflow is installed
2. discover → list recent local Claude / Codex / trial sessions
3. pick → user chooses one (or confirms your recommendation)
4. view → open the viewer with --confirm and give them the localhost URL
5. confirm → wait for the Approve button (or their chat reply)
6. submit → you upload; report Submitted / Already submitted + digest
7. persist → if this repo has no local copy of this skill, write oneAlways make sure the latest BenchFlow is installed before anything else —
bench traj setup and the session-JSONL viewer only exist in 0.7.1+:
uv tool install --python 3.12 --upgrade benchflowIf uv reports Executables already exist, rerun with --force. Verify that
bench --version reports at least 0.7.1. If the installed CLI lacks
bench traj setup or cannot open a session JSONL in the viewer, upgrade
first rather than working around it.
Prefer the listing the CLI already knows how to make:
bench traj setup --listIf that command is missing, search these locations and skip nested
subagents/ files unless the user asks:
~/.claude/projects/**/*.jsonl~/.codex/sessions/**/*.jsonl and ~/.codex/archived_sessions/*.jsonl~/.cursor/projects/*/agent-transcripts/**/*.jsonl~/.local/share/opencode/opencode.db (run opencode db path to confirm);
older versions used JSON files under ~/.local/share/opencode/storage/session/jobs/**/trajectory/ or a directory with turn*.txtIf the user described a time window or topic (for example, sessions from the last 72 hours on a specific project), prefer sessions matching that description.
Show the 8 most recent with mtime, path, and the first user-prompt snippet. Skip sessions that clearly contain private or proprietary work unless the user names them. If the user already named a file or folder, skip discovery.
Recommend one. Ask which to open if more than one is plausible. Do not upload yet — the viewer is how they decide the session is the one they meant.
First stage a dry run so you can show the user what upload-time redaction would mask for them (nothing is uploaded):
bench traj upload /path/to/session.jsonl --dry-runIts output ends with a plain Masked for you: ... line (for example
Masked for you: 2 API keys, 1 bearer token, or
Masked for you: nothing — no secrets detected). Extract the text after
Masked for you: — call it the masking summary.
Then open the viewer with the in-page confirm bar and tell the user the URL, passing the masking summary so it renders next to the Approve button:
bench eval view /path/to/session.jsonl --confirm --port 8889 \
--redaction-summary "2 API keys, 1 bearer token"The viewer shows the ORIGINAL session (it does not redact); the
--redaction-summary note tells the reviewer what the upload step will mask.
If the installed CLI rejects --redaction-summary (older than 0.7.2), drop
the flag and state the masking summary in chat instead.
That path may also be a trial directory. If the port is taken, pick another.
With --confirm the page shows an Approve & submit / Not this one
bar. When the user clicks, the server prints one line to stdout —
DECISION: approved or DECISION: rejected — and exits (exit code 0 on
approve, 3 on reject). Run the command so you can wait on that output:
either start it in the background and poll its output for the DECISION:
line, or run it blocking with a generous timeout.
If the installed CLI predates --confirm (bench --version below 0.7.2),
run the plain bench eval view /path/to/session.jsonl in the background
instead and rely on the chat confirmation in Step 5.
Ask them to review the page and click a button in the viewer:
DECISION: approved (exit 0) → they approved; proceed to Step 6.DECISION: rejected (exit 3) → they want a different session; go back to
pick.--confirm (older CLI), wait until they say in chat that it looks
good.Do not upload until one of those signals says the session is right.
The upload is tagged with the repository the session was about: the CLI reads
the session's recorded working directory (only the session's own cwd — never
the directory you run the upload from), resolves its git origin remote, and
stores repo/<owner>/<name> as the source id (it prints
Repo: owner/name (from session cwd /path; use --no-repo to omit) — the
local path is terminal output only; run --dry-run to see the tag
beforehand). Sessions recorded outside a git repo upload untagged. Mention
the detected repo when you ask for confirmation — "This session will be
tagged repo/owner/name; say the word if you want it omitted" — so they can
opt out for private repos.
Before upload, remind them not to submit secrets, and repeat the masking summary from the Step 4 dry run when asking for approval — "Before upload, BenchFlow masks: 2 API keys, 1 bearer token; originals never leave this machine" — so they know exactly what redaction handles for them. The CLI masks detected secret values locally before anything leaves the machine (the server independently rescans and rejects any survivor), but redaction is a safety net, not a license to upload credentials.
You run the upload. The CLI infers GitHub username and email from gh /
git; when identity resolves, the upload runs without prompts. If inference
fails, ask for both in chat and pass --github-id / --email. Do not tell
the user to re-run a command.
bench traj upload /path/to/session.jsonlIf the user declined the repo tag in the confirm step, add --no-repo.
If the first request times out, run the same upload again. Retries are safe because the digest is content-addressed. Report Submitted or Already submitted, plus the digest.
If this project does not already have
.agents/skills/benchflow-traj-upload/SKILL.md (or a .claude/skills /
.codex/skills copy), write this skill there so the next agent does not
rediscover the loop. Do not overwrite a newer local copy.
© benchflow-ai, Apache-2.0. 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 1 other file in .agents/skills/benchflow-traj-upload of benchflow-ai/benchflow.
Open the folder on GitHubat commit e965eee
Benchflow Traj Upload 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 |
|---|---|---|---|---|---|---|
| Benchflow Traj Upload this skillbenchflow-ai/benchflow | 353 | — | ~1.9k | Automated safety check: Notes | Apache-2.0 | |
| File Uploadsdavila7/claude-code-templates | 32k | 4 repos | ~238 | Automated safety check: Pass | MIT | |
| File Upload Accessibilitythedaviddias/Front-End-Checklist | 74k | — | ~418 | Automated safety check: Pass | MIT | |
| Upload R2remotion-dev/remotion | 62k | — | ~535 | Automated safety check: Notes | Custom licence | |
| Hunt File Uploadsickn33/agentic-awesome-skills | 47k | 1 repos | ~2.4k | Automated safety check: Pass | MIT | |
| Upload Element Previewsremotion-dev/remotion | 62k | — | ~265 | Automated safety check: Pass | Custom licence |
davila7/claude-code-templates
Expert at handling file uploads and cloud storage. An agent skill from davila7/claude-code-templates.
thedaviddias/Front-End-Checklist
A skill your agent uses when reviewing templates, rendered HTML, or shared components related to Make file uploads accessible.
remotion-dev/remotion
Upload large Remotion repository assets to the Cloudflare R2 bucket behind remotion.media and replace local public/ assets with hosted URLs.
sickn33/agentic-awesome-skills
Hunt file upload bugs
remotion-dev/remotion
Upload a Remotion Element's preview assets to remotion.media and replace local preview URLs.
zebbern/claude-code-guide
Upload files to Cloudflare R2, AWS S3, or any S3-compatible storage (like MinIO) and generate secure, time-limited presigned download links with configurable expiration, typically set to 5 minutes.
benchflow-ai/benchflow
SkillsBench task authoring — walk a contributor from idea to submission-ready task following CONTRIBUTING.md and the task-implementation rubric.
benchflow-ai/benchflow
SkillsBench task PR review — classifies the task track (standard / research / multimodal), runs static policy checks against the track-specific rubric, benchmarks the task across oracle plus Claude…
benchflow-ai/benchflow
Review Benchflow or SkillsBench task-run trajectories and integration-test Benchflow code changes.
benchflow-ai/benchflow
Run agent benchmarks, create tasks, analyze results, and manage agents using BenchFlow.
benchflow-ai/benchflow
Operate, test, troubleshoot, and explain bench traj upload for public or trusted-direct trajectory contributions, including interactive and fully specified commands, dry runs, input validation…
benchflow-ai/benchflow
Delegate complex coding tasks to a specialist model. An agent skill from benchflow-ai/benchflow.
Find a local Claude Code or Codex session, open the BenchFlow trajectory viewer, and submit it after the user reviews it. Benchflow Traj Upload is an agent skill from benchflow-ai/benchflow. Find a local Claude Code or Codex session, open the BenchFlow trajectory viewer, and submit it after the user reviews it.
Benchflow Traj Upload fits situations like: someone pastes a BenchFlow eval prize line; wants to submit / share / contribute / upload a trajectory; set up traj upload; pick a session to send.
Run `npx skills add benchflow-ai/benchflow --skill benchflow-traj-upload -a claude-code`. Or copy the skill folder (.agents/skills/benchflow-traj-upload in benchflow-ai/benchflow) into .claude/skills/benchflow-traj-upload in your project. Claude Code loads it when a task matches its description.
Run `npx skills add benchflow-ai/benchflow --skill benchflow-traj-upload -a codex`. Or copy the skill folder (.agents/skills/benchflow-traj-upload in benchflow-ai/benchflow) into .agents/skills/benchflow-traj-upload 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 benchflow-ai/benchflow --skill benchflow-traj-upload -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/benchflow-traj-upload, .gemini/skills/benchflow-traj-upload, .github/skills/benchflow-traj-upload and .opencode/skills/benchflow-traj-upload in your project.
Going by SKILL.md and its folder, Benchflow Traj Upload needs the command-line tools its instructions call (uv and opencode). Our summary lists: Python 3. Its frontmatter pre-approves these tools: Read, Bash.
SKILL.md contains no URLs. Its commands use uv, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
Benchflow Traj Upload is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.9k tokens (SKILL.md is roughly 7.5k 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 Benchflow Traj Upload: File Uploads (davila7/claude-code-templates, 32k stars), File Upload Accessibility (thedaviddias/Front-End-Checklist, 74k stars), Upload R2 (remotion-dev/remotion, 62k stars) and Hunt File Upload (sickn33/agentic-awesome-skills, 47k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
benchflow-ai (a GitHub organization) maintains it in benchflow-ai/benchflow, which has 353 GitHub stars. The repository holds 8 skills in this directory. The repository was last updated on October 6, 2026.
Source: benchflow-ai/benchflow on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.