Borrowing it
Nothing to install: this file belongs to lowtidebuild/public-equity-research. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/lowtidebuild/public-equity-research/main/.claude/skills/data-manager/SKILL.mdgit clone --depth 1 https://github.com/lowtidebuild/public-equity-researchWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/lowtidebuild/public-equity-research/data-manager)<a href="https://agentmods.dev/skills/lowtidebuild/public-equity-research/data-manager"><img src="https://agentmods.dev/badge/skills/lowtidebuild/public-equity-research/data-manager/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/lowtidebuild/public-equity-research/data-manager"><img src="https://agentmods.dev/badge/skills/lowtidebuild/public-equity-research/data-manager.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.02347 |
| Opus 5 | $0.00000 | $0.01174 |
| Sonnet 5 | $0.00000 | $0.00469 |
| Haiku 4.5 | $0.00000 | $0.00235 |
Grade A, and why
data-manager scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 214 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data Manager — SKILL.md
Role: Step 10 (post-analysis persistence) + Workflow 3 (portfolio & watchlist management)
Triggered by: CLAUDE.md after Step 9 (quality check) for persistence; directly for Workflow 3 commands
Reads: run-local analysis-result.json, optional run-local evidence-pack.json, optional run-local context-budget.json, output/watchlist.json, output/portfolio.json
Writes: Snapshot files, output/watchlist.json, output/portfolio.json, output/catalyst-calendar.json
References: references/snapshot-schema.md, references/watchlist-schema.md, references/portfolio-schema.md, references/catalyst-schema.md
Part A — Step 10: Post-Analysis Persistence
Run after Step 9 (quality check passes or flags applied).
Step 10.1 — Save Snapshot
python .claude/skills/data-manager/scripts/snapshot-manager.py save \
--ticker {ticker} \
--data-file output/runs/{run_id}/{ticker}/analysis-result.json
Expected output: confirms output/data/{ticker}/snapshots/{snapshot_id}/analysis-result.json created, sibling artifacts such as validated-data.json, evidence-pack.json, context-budget.json, and raw artifacts promoted when present, and output/data/{ticker}/latest.json updated as a pointer.
Snapshots persist thesis_pillars[] when present in analysis-result.json.
Legacy or analyst-missing pillars default to an empty list, but Mode A/C/D
analyses should emit 3-5 falsifiable pillars.
If script fails because the input is not schema-compliant, run:
python .claude/skills/data-validator/scripts/validate-artifacts.py --artifact-type analysis-result --input output/runs/{run_id}/{ticker}/analysis-result.json
If legacy artifacts must be persisted temporarily, use --skip-validation explicitly and treat the snapshot as a compatibility fallback.
Step 10.2 — Update Watchlist Entry (if ticker in watchlist)
Check if ticker exists in output/watchlist.json. If yes:
python .claude/skills/data-manager/scripts/watchlist-manager.py update-snapshot \
--ticker {ticker} \
--snapshot-path output/data/{ticker}/snapshots/{snapshot_id}/analysis-result.json
What ships with it
9 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/catalyst-schema.md 800 B
- references/portfolio-schema.md 5.0 KB
- references/snapshot-schema.md 11 KB
- references/watchlist-schema.md 4.2 KB
- scripts/artifact-manager.py 4.0 KB runs code
- scripts/catalyst-aggregator.py 21 KB runs code
- scripts/delta-comparator.py 22 KB runs code
- scripts/snapshot-manager.py 8.0 KB runs code
- scripts/watchlist-manager.py 8.8 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 214 lines · 0 tokens per session scan A d3b9f5aeb925
data-manager is a skill published in the GitHub repository lowtidebuild/public-equity-research (46 stars, last pushed 1mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 2,347 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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