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OpenClaw skill trust index
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vishalgojha

vishalgojha publishes 6 tracked skills in DriftBot.

Catalog decision: Mixed but usable publisher: there is meaningful evidence here, but reputation still needs to be earned skill by skill.
6
indexed skills
67
average score
0
manual reviews
0
high-risk labels
catalog evidence snapshotno baseline-v3 receipts yetno functionality-v2 receipts yetno manual reviews yetno high-risk labels
Read this row as a catalog snapshot: runtime coverage, deeper follow-on coverage, human review presence, and high-risk concentration before you compare individual skills.

📊 Runtime quality summary

Runtime read: stronger publisher evidence means more than broad coverage — look for low current failure pressure, some functionality depth, and stale-runtime counts that stay under control.
eligible runtime skills: 6latest touch: n/ano current regressions
Baseline coverage
00% of eligible skills have baseline-v3 receipts
Baseline pass rate
0%0 passed · 0 currently failing
Functionality coverage
00% of baseline-cleared skills have functionality-v2
Fixture-backed rate
0%0 functionality-v2 rows have richer fixture/example proof
Stale baseline rows
0baseline receipts older than 7 days
Functionality failures
0current failed functionality-v2 rows in the latest publisher state

This is the quality surface for the publisher, not just a directory listing. It shows how much of the catalog has real receipts, how often those receipts are passing, whether richer fixture-backed proof exists, and whether the publisher currently carries regressions, reproduced failures, or stale runtime evidence.

Latest runtime touch: n/a. Publisher-level summaries do not replace skill-level review, but they do make reputation more earned: a publisher with broader coverage, stronger pass rates, and fixture-backed proof looks different from one living on thin smoke tests.

If you want the system-wide view, open the runtime dashboard. If you want the scoring logic, read the methodology.

Fresh runtime sliceStale runtime slice

No runtime receipts for this publisher yet.

Skills from this publisher

Showing 6 of 6 skills

Label mix on this page

Trusted: 6Use Caution: 0Insufficient Evidence: 0High Risk: 0

This distribution is a quick provenance cue, not a verdict. A publisher can have a mix of safer and riskier skills, so the useful move is to compare patterns here and then open the individual scorecards.

Publisher profiles are best for spotting catalog patterns: repeated shell access, common external services, whether manual review exists, and whether higher-risk labels are isolated or widespread.

On this page: 6 source-scanned, 0 catalog-only, and 0 manually reviewed entries in the current slice.

If you want the scoring logic, read the methodology. If you want the broader landscape, go back to the full index.

lead-storage

vishalgojha · vsource-scanned
69
overall

Persist validated lead objects through write-only storage operations after Supervisor provides explicit confirmation. Use when users ask to save approved leads to Google Sheets or DB, including normalized location and priority fields. Recommended chain end: supervisor confirmation then lead-storage. Do not use for parsing, extraction, analytics, or action recommendation.

Trustedconfidence: source evidencesource-scanned
+ 1 more
privileged capability
Take: Source-aware scan found higher-privilege capability areas (token), but that alone is not evidence of malicious behavior.
Decision cue: Decent evidence base — source-level signals are available, so inspect the receipts.

action-suggester

vishalgojha · vsource-scanned
68
overall

Generate non-binding follow-up action suggestions from lead summaries or lead lists. Use when users ask for next best actions, call list for hot leads, or follow-up draft plan without automatic execution. Recommended chain: summary-generator then action-suggester then supervisor approval. Do not use for parsing, storage, or autonomous action execution.

Trustedconfidence: source evidencesource-scanned
+ 1 more
privileged capability
Take: Source-aware scan found higher-privilege capability areas (email), but that alone is not evidence of malicious behavior.
Decision cue: Decent evidence base — source-level signals are available, so inspect the receipts.

sentiment-priority-scorer

vishalgojha · vsource-scanned
68
overall

Score normalized real-estate leads using sentiment, urgency, intent, recency, and record type to produce deterministic priority rankings and P1-P3 buckets. Use when users ask to prioritize hot leads, rank callback queue, or triage follow-ups without performing writes or outbound sends. Recommended chain: india-location-normalizer then sentiment-priority-scorer then summary-generator and action-suggester.

Trustedconfidence: source evidencesource-scanned
+ 1 more
privileged capability
Take: Source-aware scan found higher-privilege capability areas (token), but that alone is not evidence of malicious behavior.
Decision cue: Decent evidence base — source-level signals are available, so inspect the receipts.

india-location-normalizer

vishalgojha · vsource-scanned
67
overall

Normalize Indian real-estate location text into canonical city and locality fields (Mumbai and Pune v1) with confidence and unresolved flags. Use when leads contain aliases like Goregaon, Andheri W, PCMC, Hinjewadi, Baner, or Wakad. Recommended chain position: lead-extractor then india-location-normalizer then sentiment-priority-scorer. Do not use for writes or outbound actions.

Trustedconfidence: source evidencesource-scanned
+ 1 more
privileged capability
Take: Source-aware scan found higher-privilege capability areas (token), but that alone is not evidence of malicious behavior.
Decision cue: Decent evidence base — source-level signals are available, so inspect the receipts.

lead-extractor

vishalgojha · vsource-scanned
66
overall

Extract structured real-estate lead records from parsed message objects. Use when users ask to find leads in WhatsApp exports, extract name-phone-budget, or classify listing vs requirement posts. Recommended chain: run after message-parser and before india-location-normalizer. Do not use for storage, summaries, outbound messaging, or action execution.

Trustedconfidence: source evidencesource-scanned
+ 1 more
privileged capability
Take: Source-aware scan found higher-privilege capability areas (token, whatsapp), but that alone is not evidence of malicious behavior.
Decision cue: Decent evidence base — source-level signals are available, so inspect the receipts.

message-parser

vishalgojha · vsource-scanned
63
overall

Parse raw WhatsApp exports (TXT or JSON) into normalized message objects with `timestamp`, `sender`, and `content`. Use when users ask to parse chat export, clean WhatsApp dump, or convert chat TXT to structured JSON before extraction. Recommended chain start: message-parser then lead-extractor. Do not use for lead interpretation, storage, summarization, or action suggestions.

Trustedconfidence: source evidencesource-scanned
+ 1 more
privileged capability
Take: Source-aware scan found higher-privilege capability areas (whatsapp), but that alone is not evidence of malicious behavior.
Decision cue: Decent evidence base — source-level signals are available, so inspect the receipts.
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Trust reading guide

Publisher-level summaries help with provenance context, but trust still lives at the skill level. Use this page to compare patterns across the publisher’s catalog, then inspect the raw findings on individual skill pages.

Back to the full index