Imported from starchild-ai-agent/official-skills (temp-files/SKILL.md). Install upstream with npx skills add starchild-ai-agent/official-skills --skill temp-files. Copyright stays with the author.

Temp-Files — Workroom file relay

This skill lets one agent drop temporary files, directories, or whole-site snapshots to another agent without polluting the long-term backup namespace and without an external file host.

Every command hits the same service (sc-agent-backup.internal) and authenticates with the container's built-in CONTAINER_JWT. Identity and path are derived from the JWT: user_id = JWT.userInfoID, agent_scope = JWT.containerId (defaults to default). You cannot reach, see, or delete relay files belonging to another user or another agent.

Difference vs. the backup skill (must read)

Never mix the two. "Restore an entire agent state" → use backup. "Hand off one artifact so the other agent can carry on" → use this skill.

Operational rules

Rule 1 — Do not use the relay as a file host

Default file TTL is 7 days. Even with overwrite/download sliding renewal, the hard cap is 60 days. Anything that needs to stick around goes through backup or volume-backup.

Rule 2 — Path whitelist

The server only accepts segments matching [A-Za-z0-9._\- ]. It rejects .., absolute paths, empty segments, and control characters. Just pass a relative path:

• skills/my-skill/SKILL.md ✅
• sites/staging/index.html ✅
• ../escape.txt ❌ → 400 bad_path
• /abs/oops.md gets its leading slash stripped — better not to send it

Rule 3 — Short links are "agent-to-agent inside", not public sharing

The first-pass short link follows a capability URL model:

• Whoever holds tf_xxxxxxxx can fetch it (the code itself is the credential — 64 bits of entropy)
• But still requires the 6PN internal network + a valid CONTAINER_JWT (for audit)
• A browser or bare curl has no token, so it gets 401 — that's expected, not a bug
• Cross-user agents can fetch, because that is exactly the Workroom handoff use case

Correct flow:

1. Agent A calls /tf put to upload
2. Agent A calls /tf link and receives tf_xxxxxxxx
3. Agent A sends the short link to agent B over Workroom
4. Agent B (inside Fly, with its own CONTAINER_JWT, possibly under a different user) calls tf fetch tf_xxxxxxxx to retrieve it

Do not hand http://sc-agent-backup.internal:8080/t/<code> to an end user to open in a browser — it isn't publicly reachable. If/when public sharing ships, wait for the phase-B public resolver.

Cleanup rule: once the receiver confirms they have the file, the sender should immediately tf unlink <code> to revoke the short link and stop the token from lingering. Sensitive content must be unlinked — don't rely on TTL as a backstop.

Rule 4 — Stop on failure, do not silently retry

If any tf.py subcommand exits non-zero, stop immediately and return the stderr verbatim to the user. Do not "let me try again for you."

Install path

The skill installs into /data/workspace/skills/temp-files/. Every command runs from the agent's working directory:

python3 skills/temp-files/scripts/tf.py <subcommand> ...

Command reference

Environment for every command:

• CONTAINER_JWT — injected by ai-agent, required
• TEMP_STORAGE_URL — optional, defaults to http://sc-agent-backup.internal:8080

Global output switches (place before the subcommand):

• --verbose: emit full payload / error meta (for debugging)
• --json: stable JSON envelope, same keys on success and failure
  • success: {ok: true, error: "", message: "ok", detail: "", data: {...}}
    • data defaults to the command's compact view (minimum useful field set)
    • with --verbose, data becomes the server's raw payload (all fields)
  • failure: {ok: false, error: "<code>", message: "...", detail: "...", exit_code: N}
    • error is the server's error code (e.g. bad_path / not_found / quota_exceeded) or usage_error / http_error
    • with --verbose, includes a meta sub-structure (HTTP status / server's original message+detail)
• default (no switches): compact output, the smallest useful set of fields (readable by humans and agents alike)

Note: tf list and tf links without --json print a human-friendly table; with --json they go through the envelope and data carries the full entries/links array.

Recommended defaults (quick reference)

A. Upload / overwrite

python3 skills/temp-files/scripts/tf.py put <local-file> <remote-path> \
    [--ttl-days N]

Example:

python3 skills/temp-files/scripts/tf.py put ./SKILL.md skills/demo/SKILL.md
# → {"path": "...", "size_bytes": ..., "expires_at": ...}

Same-name uploads overwrite; the response returns a fresh expires_at.

B. List

python3 skills/temp-files/scripts/tf.py list [--prefix PATH]

No --prefix lists the root; --prefix sites/ lists one level under that.

C. Download

# Single file
python3 skills/temp-files/scripts/tf.py get <remote-path> <local-dest>

# Whole directory as a zip
python3 skills/temp-files/scripts/tf.py get <remote-dir> <local-dest.zip> --zip

A successful download slides the TTL forward by 7 days.

D. Delete

# Single file / empty directory
python3 skills/temp-files/scripts/tf.py rm <remote-path>

# Non-empty directory
python3 skills/temp-files/scripts/tf.py rm <remote-dir> --recursive

E. Short links

python3 skills/temp-files/scripts/tf.py link <remote-path> \
    [--zip] [--ttl-seconds 3600]
# → {"code": "tf_xxxxxxxx", "url": "http://.../t/tf_xxxxxxxx", ...}

# List currently active short links
python3 skills/temp-files/scripts/tf.py links

# Revoke
python3 skills/temp-files/scripts/tf.py unlink <code>

Short link TTL defaults to 1 hour and caps at 7 days (independent of the file's own TTL).

F. Pull data via a short link (what the receiving agent runs)

# Download + auto-unpack (strongly recommended)
python3 skills/temp-files/scripts/tf.py fetch <code> <local-dest> --extract

# Or specify the extract directory
python3 skills/temp-files/scripts/tf.py fetch <code> ./pack.zip --extract ./out

# Without --extract: download only, no unpack
python3 skills/temp-files/scripts/tf.py fetch <code> <local-dest>

Any caller with a valid CONTAINER_JWT can fetch (cross-user is fine).

Zip auto-detect: when the server returns Content-Type: application/zip, fetch and get automatically rename the local file to end in .zip and tell you in the JSON output via "kind": "zip".

Auto-unpack (--extract):

• Uses Python's built-in zipfile / tarfile; no dependency on system unzip/7z
• Supported formats: .zip / .tar / .tar.gz / .tar.bz2 / .tar.xz (detected by magic bytes, not the file suffix)
• Built-in zip-slip / tar-slip defence: .. segments are rejected; symlink members are rejected
• With no value: extracts to a sibling directory (archive name minus suffix); with a value: extracts into the specified directory
• After a successful extract, the JSON output includes extracted_kind / extracted_to / extracted_top

Example JSON output (with --extract):

{
  "saved": "output/tf_from_4814.zip",
  "kind": "zip",
  "bytes": 7363,
  "sha256": "...",
  "content_type": "application/zip",
  "server_filename": "temp-files-share.zip",
  "extracted_kind": "zip",
  "extracted_to": "output/tf_from_4814",
  "extracted_top": ["temp-files-share/"]
}

So the receiving agent should:

1. Call fetch with --extract by default
2. Read extracted_to from the stdout JSON — files live in that directory
3. If the JSON contains extract_skipped or extract_error, fall back to the saved path and handle it manually based on kind

Typical scenarios

Scenario 1: agent A hands a skill to agent B for testing

# A:
python3 skills/temp-files/scripts/tf.py put ./my-skill.zip skills/my-skill.zip
python3 skills/temp-files/scripts/tf.py link skills/my-skill.zip --ttl-seconds 3600
# Receive tf_xxxxxxxx, post it to B in Workroom

# B: (recommended: fetch + auto-unpack in one shot)
python3 skills/temp-files/scripts/tf.py fetch tf_xxxxxxxx ./inbox.zip --extract
# The fetch JSON already includes sha256 — no need to rerun sha256sum
# cd into JSON.extracted_to to test; write a report
python3 skills/temp-files/scripts/tf.py put ./test-report.md reports/test-report.md
python3 skills/temp-files/scripts/tf.py link reports/test-report.md --ttl-seconds 1800
# Send the report short link back to A

# Once A has the report:
python3 skills/temp-files/scripts/tf.py unlink tf_xxxxxxxx  # revoke the original skill short link

Scenario 2: agent A hands a staging site to agent B

# A:
cd ./staging-site/
python3 skills/temp-files/scripts/tf.py put-dir . sites/foo --ttl-days 14
python3 skills/temp-files/scripts/tf.py link sites/foo --zip
# B receives a directory-zip link

# B:
python3 skills/temp-files/scripts/tf.py fetch tf_xxxxxxxx ./foo.zip --extract
cd ./foo
# Edit, then push back
python3 skills/temp-files/scripts/tf.py put-dir . sites/foo

Security boundary cheatsheet

• 6PN only: the service returns 403 on the public internet
• JWT must be valid and type ∈ {container, access}
• Each user has an isolated namespace; each agent under that user has its own sub-scope
• Direct path access at /temp-files/... is user-isolated (you cannot reach others')
• Short links at /t/<code> are capabilities: anyone with the code can fetch (still requires 6PN + any valid JWT for audit)
• Paths reject .. and control characters
• Per-file limit 200 MB, per-user quota 2 GiB (server-tunable)

Common errors / troubleshooting

Read ERROR + DETAIL first, then decide whether it's a parameter problem, a permission problem, or a missing object. If a command exits non-zero, follow the house rule: stop, do not silently retry.

Minimal regression checklist (P1 gates)

After every CLI output or error-handling change, run at least these five:

1. Default output is compact (without --verbose), yet put/get/fetch still include sha256 and link still includes url
2. --verbose emits the full field set (envelope's data = server's raw payload)
3. --json on success has every key: ok, error, message, detail, data
4. --json on failure has every key: ok, error, message, detail, exit_code (where error is the server error code)
5. Exit codes stay consistent: success = 0, business failure = 1, usage error = 2
6. tf --json list and tf --json links go through the envelope (don't let the subparser's --json override)

Quick triage flow (share with collaborators)

1. tf list --prefix <target-prefix>: confirm the object actually exists.
2. Preserve the original stderr from the failing command (especially DETAIL:).
3. On 4xx: fix the arguments — do not retry the same command.
4. On 5xx / network error: wait briefly, then retry once.

Notes

• File TTL defaults to 7 days; downloads/overwrites each renew by 7 days; hard cap 60 days
• Short link TTL defaults to 1 hour, capped at 7 days
• To force a shorter TTL: pass --ttl-days 1 on upload (still bounded by the horizon)
• Directory-zip default caps: 5000 files / 500 MB; over either limit → 413