Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add lourencomaciel/sift-gateway --skill openclawgit clone --depth 1 https://github.com/lourencomaciel/sift-gatewayWrote 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/lourencomaciel/sift-gateway/openclaw)<a href="https://agentmods.dev/skills/lourencomaciel/sift-gateway/openclaw"><img src="https://agentmods.dev/badge/skills/lourencomaciel/sift-gateway/openclaw/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/lourencomaciel/sift-gateway/openclaw"><img src="https://agentmods.dev/badge/skills/lourencomaciel/sift-gateway/openclaw.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00021 | $0.00837 |
| Opus 5 | $0.00010 | $0.00418 |
| Sonnet 5 | $0.00004 | $0.00167 |
| Haiku 4.5 | $0.00002 | $0.00084 |
Grade A, and why
reliable-tool-context 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 — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reliable Tool Context
Use this skill to build reliable tool context whenever command output will be analyzed by the model and correctness matters. Capture once, query from artifacts, and return compact answers without copying raw payloads into model context.
CLI Decision Rule
Use Sift to establish reliable tool context when any of these are true:
- Output will be consumed by the model (analysis, transformation, or follow-up querying).
- Pagination exists or may exist (
pagination.next.kind=="command"). - JSON schema/root confidence is low, or rows may be heterogeneous (even for small payloads).
- You need reproducibility, redaction discipline, or auditability.
Use direct CLI only when all of these are true:
- Output is clearly small.
- Schema/root path is obvious.
- It is a one-off human inspection with no follow-up model reasoning.
Required workflow
- Capture output as an artifact:
sift-gateway run --json -- <command>
- Keep only
artifact_idplus a short summary in prompt context. - Handle pagination explicitly only when present. If
pagination.next.kind=="command", continue with:
sift-gateway run --json --continue-from <artifact_id> -- <next-command-with-next_params-applied>
- Query artifacts with explicit root path and compact output:
sift-gateway code --json <artifact_id> '$' --code "def run(data, schema, params): return [{'id': row.get('id'), 'status': row.get('status')} for row in data[:20]]"
- Resolve root path from response hints, not guesswork:
- Current
runbehavior uses canonical root path$; use$for follow-up code queries. - If
response_mode=="schema_ref"andschemasare present, use schemaroot_pathas the source of truth. - Treat
sample_itemas a preview row only.
Schema discovery protocol
- Do not use
jq '.[0]'(or equivalent "first-item" shortcuts) to infer schema or root path. Many payloads are object-wrapped, have multiple candidate roots, or include heterogeneous rows where first-item heuristics are misleading. - In Sift responses,
sample_itemis emitted only when Sift can verify consistent item shape across the resolved list. Ifsample_itemis absent, inspectschemas; for currentruncaptures, schemaroot_pathshould be$. - If
sample_item_text_truncatedis true, treat long text fields as truncated previews and confirm details with a focused code query.
What ships with it
1 file 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.
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 · 81 lines · 21 tokens per session scan A f242c15caec4
reliable-tool-context is a skill published in the GitHub repository lourencomaciel/sift-gateway (31 stars, last pushed 1mo ago), licensed MIT. It adds 21 tokens to every session and 837 once invoked, about $0.0001 per session on Opus 5. 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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