BB session-context-injector
Reorient a Telegram chat after a session reset. Reads a project's STATUS.md (resume point, blockers, next action) and sends a project-specific context injection message via the Telegram bot API. Use when: clearing session transcripts, creating new project rooms, or onboarding collaborators into a scoped chat. Supports 3 message variants: group refresh, direct DM summary, and new-room welcome.
Reorient a Telegram chat after a session reset.
As a process B 65/100 · Nearly there — weak spots: result and completion, when it triggers, running it twice
How to improve
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 2
✓ No critical or high findings
Medium and low: 2
-
low Exfiltration
exfil-webhook-urlskill-card.md:40Webhook / callback URL commonly used for exfiltration (verify the destination) (documentation of a security skill; the skill's own vendor host)- [Telegram Bot API sendMessage endpoint](https://api.telegram.org/bot{bot_token}/sendMessage)security skillvendor-host
A further 1 matches are quotations in this security skill's documentation and are not counted as findings.
Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 65/100
- 0Result and completion. Does not say what the result is
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 8 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Tools and files. No external tools needed
- 100Steps. 9 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1946 tokens
- 100Progress reporting. Reports progress
- low 12 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (3 tags): a typed call is more reliable
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 395: enough signal without eating the budget
- +4Structure: 13 headings
- +3Step-by-step instructions: 9 items
- +4Has examples (8 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.