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scrape-competitor-pricing-weekly

Watches your competitors' pricing each week and flags changes.
description: "Triggers on prompt mention of 'scrape-competitor-pricing-weekly'."
personal 2 files 10 recent evals

What it does for you

Watches your competitors' pricing each week and flags changes.

What it produces

A recent result, so you can see the kind of work it returns.

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How to get it

These run inside the Snappy workspace. Want this working in your business? I set skills like this up with you, in one focused week.

Work with me
For developers how this skill is built, graded, and how it runs

at a glance- the short version

eval modeauto
categoryKnowledge
stages2
dependsbrowse

what's inside - the parts that make up a skill 2/4 present

A skill is just a few plain-text files. Only the main one is required. The rest are optional, added as the work needs them. This is what the skill is made of; how it runs is just below.

The skill
state/skills/scrape-competitor-pricing-weekly/SKILL.md present
the skill itself, in plain text
The main file. It says what the skill is and lays out the steps in plain English.
Code
state/lib/scrape-competitor-pricing-weekly.ts not present
code the skill can run
Optional. Many skills are just words and need no code at all.
Scripts
state/bin/scrape-competitor-pricing-weekly/ not present
helper scripts
Optional. Added when a skill has a few commands to run.
Loader
state/skills/scrape-competitor-pricing-weekly/AGENTS.md present
what the AI loads on the fly
Loaded automatically the moment this skill is needed. Kept short on purpose.

how it's graded - what counts as a good run 4 criteria · 2 deterministic · 2 judge

Each row is one thing a good run has to get right. deterministic means a quick check decides, pass or fail. judge means the AI reads the result and rates it. Grading each piece on its own (instead of one overall score) shows exactly where a run fell short, so the fix is obvious.

name
kind
check
all_competitors_processed
judge
The skill logs indicate that pricing pages for all competitors listed in 'sources/competitors.json' were fetched and processed.
new_snapshot_saved
deterministic
A new pricing snapshot for the current week is present in 'state/log/competitor-pricing/'.
pricing_changes_logged
judge
If any pricing changes were detected by comparing against last week's snapshot, a clear delta was logged, including which competitor and specific changes.
eval_row_appended
deterministic
The log via 'state/lib/log.ts' contains an entry for 'scrape-competitor-pricing-weekly' with 'ok', 'checked', and 'changed' fields.

how it runs - the shared frame every skill uses 3/5 present

Every skill runs the same way. One part does the work, a separate part checks it, and a short loader hands the AI exactly what it needs for the job. Anything this skill doesn't use shows a one-line note saying why, on purpose, not by accident.

makes the work The worker
inferred
cron-driven; manual via from the run command
No worker is named directly, so the command this skill runs is treated as the worker.
checks the work The reviewer
not present

No separate check found. Without one, the part that makes the work could end up approving its own work, worth a closer look.

frame
learns Self-correction
present
fixes itself learns from gaps
When a run hits a gap, the skill gets edited on the spot [FIXED] or queued for a bigger rewrite [LOGGED], so it keeps getting better.
tidies up Background fixes
present
queued for rewrite runs in the background
Bigger fixes that can't be made on the spot get queued and rewritten in the background later.
remembers Run history
present
state/log/evals.ndjson unknown runs
Every run is written down here, so the next time this skill is used it already knows how the last runs went.
Critical rules the things this skill must not get wrong
  1. ALWAYS read the competitor list from sources/competitors.json (human-owned). If missing, CREATE it — do not invent competitors inline.
  2. ALWAYS save this week's snapshot to state/log/competitor-pricing/ BEFORE comparing — partial run with no snapshot loses the baseline for next week.
  3. NEVER fan out parallel agent-browser fetches against one session — DOM-mutation agents drop writes silently. Serialize.
  4. Score 0.5 if some competitors fetched (partial). Score 0.0 only if NONE could be reached (likely auth or network).

what it has learned - fixes written back in over time sample

When a run hits something this skill didn't handle, the fix gets written back into the skill so it doesn't happen again. FIXED means it was corrected on the spot. LOGGED means it's queued for a bigger rewrite. Either way, the skill gets a little better and never makes the same mistake twice.

  1. Loading feedback rows…

how the work flows- step by step

inputs browse
1 generator
invoke
cron-driven; manual via `state/lib/log.ts` `append("scrape-competitor-pricing-weekly", { ok, checked, changed })`
2 data
eval log
`state/log/evals.ndjson` (skill: "scrape-competitor-pricing-weekly")

SKILL.md- the skill, written out in plain English

scrape-competitor-pricing-weekly

Backed by: agent-browser MCP for fetch + state/lib/log.ts for the eval row.

Cron job (Saturday 9 AM). Checks competitor pricing pages for changes.

Steps

  1. Read the competitor list from sources/competitors.json (create if missing).
  2. For each competitor URL, fetch the pricing page via agent-browser.
  3. Extract pricing tiers and amounts.
  4. Compare against last week's snapshot in state/log/competitor-pricing/.
  5. If any prices changed, log the delta.
  6. Save this week's snapshot.
  7. append("scrape-competitor-pricing-weekly", { ok, checked, changed }) via state/lib/log.ts.

Eval

Score 1.0 if all competitors checked and snapshot saved. Score 0.5 if some competitors checked. Score 0.0 if no competitors could be reached.

Rubric

criteria:
  - name: all_competitors_processed
    kind: judge
    check: "The skill logs indicate that pricing pages for all competitors listed in 'sources/competitors.json' were fetched and processed."
  - name: new_snapshot_saved
    kind: deterministic
    check: "A new pricing snapshot for the current week is present in 'state/log/competitor-pricing/'."
  - name: pricing_changes_logged
    kind: judge
    check: "If any pricing changes were detected by comparing against last week's snapshot, a clear delta was logged, including which competitor and specific changes."
  - name: eval_row_appended
    kind: deterministic
    check: "The log via 'state/lib/log.ts' contains an entry for 'scrape-competitor-pricing-weekly' with 'ok', 'checked', and 'changed' fields."

AGENTS.md- what the AI loads when this skill comes up

scrape-competitor-pricing-weekly - loader

Per-turn rules for the scrape-competitor-pricing-weekly skill. Full reference: state/skills/scrape-competitor-pricing-weekly/SKILL.md.

Critical Rules

  • ALWAYS read the competitor list from sources/competitors.json (human-owned). If missing, CREATE it - do not invent competitors inline.
  • ALWAYS save this week's snapshot to state/log/competitor-pricing/ BEFORE comparing - partial run with no snapshot loses the baseline for next week.
  • NEVER fan out parallel agent-browser fetches against one session - DOM-mutation agents drop writes silently. Serialize.
  • Score 0.5 if some competitors fetched (partial). Score 0.0 only if NONE could be reached (likely auth or network).

Commands

| ui dashboard | state/skills/scrape-competitor-pricing-weekly/resources/ui.openui | |invoke: cron-driven; manual via state/lib/log.ts append("scrape-competitor-pricing-weekly", { ok, checked, changed }) |fetch: agent-browser MCP (the documented exception lives in browser libs, not snappy-os core) |eval log: state/log/evals.ndjson (skill: "scrape-competitor-pricing-weekly")

OpenUI Resource

  • Skill-owned OpenUI Lang resource: state/skills/scrape-competitor-pricing-weekly/resources/ui.openui. Read it before rendering or editing this skill's generated component surface.
  • Treat this resource as a first-class artifact of the skill, not a generic chat response. Improve it when the skill's user-facing output needs to become richer.
  • System resources compose OpenUI primitives and inherit SnappyChat tokens. Use ui_contract: branded in SKILL.md only for deliberate platform or client visuals.

Known Pitfalls

  • sources/competitors.json is human-owned (per program.md three-layer rule). Do not auto-edit; create the file if absent and tell the operator.
  • Pricing pages move tier names around between weeks - extract by amount, not by tier label.
  • Cron fires Saturday 9 AM. Manual triggers should also tag the eval row so the cron history stays clean.

Self-Test

An agent reading this should correctly:

  1. [ ] Refuse to invent competitors; create sources/competitors.json instead
  2. [ ] Save this week's snapshot before comparing to last week
  3. [ ] Serialize browser fetches (no parallel)

Self-report

If this loader fell short, append a line:

echo "[$(date -u +%FT%TZ)] scrape-competitor-pricing-weekly: <what was missing>" >> state/log/loader-feedback.log

<!-- kernel-ok: historical attribution for the PID-loader pattern. -->

Self-correcting loader (PID feedback)

This is the rule that makes loaders learn. Ported from snappy-kernel, where it demonstrably worked: the snappy-dom-cartographer skill mapped Skool admin UI once, every later ship-agent inherited the full map for free.

Before you finish, do two things:

1. Fix gaps (P - proportional). MANDATORY. If this loader didn't cover your case - if you had to read another file, run an undocumented command, work around a wrong selector, or discover a quirk - you MUST attempt an Edit to this AGENTS.md before you log.

  • Default action: edit this file. Surgical. Add the missing line, table

row, or code example where it belongs. No restructuring.

  • Only LOGGED is allowed when: the fix needs >10 lines, spans multiple

files, or requires a structural rewrite. In that case the state/regen/drain.sh queue picks it up asynchronously.

  • "I didn't have time" / "it's minor" / "the next agent will figure it out"

are NOT valid reasons. Minor gaps compound - that's the whole point of this loop.

  • Concrete example of a valid P-fix: discover agent-browser screenshot

takes path positionally not as --output <path>. One line in a table. Edit it in. Do not just log it.

  • The goal: the next agent never has to leave the loader.

2. Log the result.

echo "[$(date -u +%FT%TZ)] scrape-competitor-pricing-weekly: <what was missing or fixed> [FIXED|LOGGED]" >> state/log/loader-feedback.log
  • FIXED = you patched this loader inline (P-fix).
  • LOGGED = too large for inline; the PostToolUse enqueue + Stop-hook drain

will rewrite the loader from scratch on next session-end.

Do not skip this. Every agent run must leave the system better than it found it. The loader is the setpoint; you are the sensor; the gap is the error signal; closing the gap is the correction.

api.ts- the code it can call

⚠ no api.ts - this skill has no typed action surface

scripts- helper scripts it can run

prose-only skill - 1 inline code block live in SKILL.md above (no state/bin/ sidecar yet).

how we check it- the checks, plus the last 10 runs

rubric auto no rubric declared
recent mean 1.00 · 10 runs actor/auditor: unverifiable
deps browse
timestamp verb score primary_issue artifact
2026-04-25 04:11Z - 1.00 - -
2026-04-21 15:58Z - 1.00 - -
2026-04-21 15:57Z - 1.00 - -
2026-04-21 03:53Z - 1.00 - -
2026-04-25 04:11Z - 1.00 - -
2026-04-21 15:58Z - 1.00 - -
2026-04-21 15:57Z - 1.00 - -
2026-04-21 03:53Z - 1.00 - -
2026-04-25 04:11Z - 1.00 - -
2026-04-21 15:58Z - 1.00 - -