agentleFS
jezwebjezweb/vite-flare-starter/skills/route-finding/SKILL.md

route-finding

Skill49 starsChanged 3 months agoMITView on GitHub

SessionEnd hook for routines emitting findings — picks the right channel (inbox_add / notify / approval_queue / space_send / webhook_post) and writes a short run-summary line. Routine-only.

Files
SKILL.md

Route Finding

Purpose

This skill is loaded as a SessionEnd hook by routines that emit findings. The main agent has just finished a run and produced text + tool calls. Your job is to:

  1. Decide which output channel(s) the finding should land in.
  2. Produce a one-line summary of what happened, suitable for the run history tail.

Channels you can reason about

The main agent already had access to these channel tools — so by the time this hook fires, they may have been called or skipped. Use the run text + tool calls to figure out what to do next, if anything:

  • inbox_add — drop a finding into the user's Inbox for them to review later. Use when the work produced a result the user should be aware of but doesn't need to act on right now.
  • notify — send a transient bell ping. Use sparingly — only for genuinely time-sensitive things ("backup failed", "deploy ready").
  • approval_queue — gate a destructive action behind human review. Use when the agent wants to send an email, post publicly, modify shared data.
  • space_send — post to a team Space. Use when the finding is collaborative — the team should see it together.
  • webhook_post — fire an external URL. Use when the finding feeds into a tool the user has set up.

Decision rules

if (no work was done OR no result worth surfacing):
  → produce a 1-line summary saying "no findings"
else if (the agent already called a channel tool):
  → just summarise what was sent + where
else if (the work suggests destructive action — sending email, posting publicly):
  → suggest approval_queue OR notify the user via inbox_add (NOT both)
else if (the work produced an informational finding):
  → suggest inbox_add with importance set per the user's stated thresholds
else:
  → just summarise; don't dispatch — sometimes nothing is the right move

Output format

You don't actually call channel tools yourself (you're a SessionEnd hook, not the main agent). Instead, return a short paragraph the routine scheduler stores as routine_runs.outputSummary. The next fire reads the most recent K of these as context — keep them dense and useful.

Format:

[outcome]: [one-sentence what-happened]. [optional: suggested next step]

Examples:

  • ok: Found 3 stuck tickets older than 7 days; emitted as inbox_add findings (medium importance). Next fire: re-check in 24h.
  • ok: No new YouTube links in #dev-chat since last run. Skipped inbox.
  • error: Could not fetch the Gmail thread (auth expired). Suggest the user reconnect Gmail in Connectors.

Tone

Terse and factual. The user reads these in a list of N runs, not in isolation. Optimise for skimmability.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.